Papers published in Journals

Number of Results: 1299

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In Press (14)

• [2981] L.B.Furstenau, Y.P. Reckziegel Rodrigues, M.K. Sott, P. Leivas, M.S. Dohan, J.R. López-Robles, M.J. Cobo, N.L. Bragazzi, K-K.R Choo. Internet of things: Conceptual network structure, main challenges and future directions. Digital Communications and Networks, in press. doi: 10.1016/j.dcan.2022.04.027
  
• [2992] X. Wu, J. Wang, Q. Li, J. Cao, E. Herrera-Viedma, Y. Guo. Trust Maintenance in IoT for Smart Cities with Complex Network Metrics. Expert Systems with Applications. Accepted, 2022, in press.
  
• [2796] W. Ding, W. Pedrycz, I. Triguero, Z. Cao, CT. Lin. Multigranulation Super-Trust Model for Attribute Reduction. IEEE Transactions on Fuzzy Systems, in press. doi: 10.1109/TFUZZ.2020.2975152
  
• [2844] P. Lázaro-Rodríguez. Noticias digitales sobre bibliotecas públicas en España: mapeo de medios y análisis temático y de consumo basado en las interacciones en Facebook.. Profesional de la Información, Accepted, 2020., in press.
  
• [2573] A. Valdivia, E. Martínez-Cámara, I. Chaturvedi, M.V. Luzón, E. Cambria, Y. Ong, F. Herrera. What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules. Journal of Ambient Intelligence and Humanized Computing (2018), in press. doi: 10.1007/s12652-018-1150-3
  Read the paper
  
  
• [2578] A. Valdivia, E. Hrabova, I. Chaturvedi, M.V. Luzón, L. Troiano, E. Cambria, F. Herrera. Inconsistencies on TripAdvisor Reviews: a Unified Index between Users and Sentiment Analysis Methods. Neurocomputing (2019), in press.
  
• [2678] P. Tellez-Dominguez, J.A. Moral-Muñoz, E. Casado, A. Salazar, D. Lucena-Anton. Efectos de la realidad virtual sobre el equilibrio y marcha en ictus: revisión sistemática y meta-análisis. Revista de Neurología, in press.
  
• [2679] M.E. Ortega-Martín, D. Lucena-Anton, C. Luque-Moreno, A.M. Heredia-Rizo, J.A. Moral-Muñoz. Aplicaciones móviles en el abordaje terapéutico del ictus: Revisión en respositorios comerciales y búsqueda de evidencia. Revista Española de Salud Pública, in press.
  
• [2597] F.J. Baldán, J.M. Benítez. Distributed FastShapelet Transform: a Big Data time series classification algorithm. Information Sciences, Accepted, in press. doi: 10.1016/j.ins.2018.10.028
  COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes
  
  
• [2171] S. Ramírez-Gallego, H. Mouriño-Talín, D. Martínez-Rego, V. Bolón-Canedo, J.M. Benítez, A. Alonso-Betanzos, F. Herrera. An Information Theory-Based Feature Selection Framework for Big Data under Apache Spark. IEEE Transactions on Systems, Man, and Cybernetics: Systems (2017), in press. doi: 10.1109/TSMC.2017.2670926
  
• [2254] P.D. Gutiérrez, M. Lastra, J.M. Benítez, F. Herrera. SMOTE-GPU: Big Data preprocessing on commodity hardware for imbalanced classification. Progress in Artificial Intelligence, in press. doi: 10.1007/s13748-017-0128-2
  
• [2361] F. Charte, A.J. Rivera, M.J. del Jesus, F. Herrera. Dealing with Difficult Minority Labels in Imbalanced Mutilabel Data Sets. Neurocomputing, 2017. Available online 14 September 2017, in press. doi: 10.1016/j.neucom.2016.08.158
  
• [2362] F. Charte, A.J. Rivera, M.J. del Jesus, F. Herrera. REMEDIAL-HwR: Tackling Multilabel Imbalance through Label Decoupling and Data Resampling Hybridization. Neurocomputing, 2017. Available online 12 September 2017, in press. doi: 10.1016/j.neucom.2017.01.118
  
• [2376] C. R. Cloninger, I. Zwir. What is the natural measurement unit of temperament: single traits or profiles?. Philosophical Transactions B, in press.
  

2025 (1)

• [3107] Y. Li, I.J. Pérez, F.J. Cabrerizo, J.A. Morente-Molinera. An algorithm for belief rule induction with partial ignorance. Expert Systems with Applications 261 (2025) 125517. doi: 10.1016/j.eswa.2024.125517
  

2024 (8)

• [3060] H. Wang, Y. Ju, P. Dong, A. Wang, F.J. Cabrerizo. Preference-based regret three-way decision method on multiple decision information systems with linguistic Z-numbers. Information Sciences 654 (2024) 119861. doi: 10.1016/j.ins.2023.119861
  
• [3063] Z. Wu, P. Gao, Y. Wang, X. Xu, N. Wan, F.J. Cabrerizo. Robust minimum cost consensus models with uncertain asymmetric costs based on linear uncertain-constrained tolerance level. Engineering Applications of Artificial Intelligence 130 (2024) 107699. doi: 10.1016/j.engappai.2023.107699
  
• [3064] X. Sun, J. Zhu, J. Wang, I.J. Pérez, F.J. Cabrerizo. Consensus-reaching process in multi-stage large-scale group decision-making based on social network analysis: Exploring the implication of herding behavior. Information Fusion 104 (2024) 102184. doi: 10.1016/j.inffus.2023.102184
  
• [3065] J.C. González-Quesada, A. Velykorusova, A. Banaitis, A. Kaklauskas, F.J. Cabrerizo. Non-uniform allocation of information granularity to improve consistency and consensus in multi-criteria group decision-making: Application to building refurbishment. Engineering Applications of Artificial Intelligence 130 (2024) 107737. doi: 10.1016/j.engappai.2023.107737
  
• [3093] Y. Li, I.J. Pérez, F.J. Cabrerizo, H. Garg, J.A. Morente-Molinera. A belief rule-based classification system using fuzzy unordered rule induction algorithm. Information Sciences 667 (2024) 120462. doi: 10.1016/j.ins.2024.120462
  
• [3094] S. Giannoukakos, S. D'Ambrosi, D. Koppers-Lalic, C. Gómez-Martín, A. Fernandez, M. Hackenberg. Assessing the complementary information from an increased number of biologically relevant features in liquid-biopsy-derived RNA-Seq datarr. Heliyon 10:6e27360 (2024). doi: 10.1016/j.heliyon.2024.e27360
  
• [3096] J. Zhang, F. Liu, Z. Liu, I.J. Pérez, F.J. Cabrerizo. Existence and simulation of multiple solutions to an optimization model for completing incomplete fuzzy preference relations. Applied Intelligence 54 (2024) 9395–9411. doi: 10.1007/s10489-024-05667-9
  
• [3100] A. Torres-Martos, A. Anguita-Ruiz, M. Bustos-Aibar, A. Ramírez-Mena, M. Arteaga, G. Bueno, R. Leis, C.M. Aguilera, R. Alcalá, J. Alcalá-Fdez. Multiomics and eXplainable artificial intelligence for decision support in insulin resistance early diagnosis: A pediatric population-based longitudinal study. Artificial Intelligence in Medicine 156 (2024) 102962. doi: 10.1016/j.artmed.2024.102962
  

2023 (41)

• [2926] R. Zhang, J. Huang, Y. Xu, E. Herrera-Viedma. Consensus models with aggregation operators for minimum quadratic cost in group decision making. Applied Intelligence 53:1370–1390. doi: 10.1007/s10489-021-02948-5
  
• [2935] J. Pereira Amorim, P.H. Abreu, A. Fernández, M. Reyes, J. Santos, M. H. Abreu. Interpreting Deep Machine Learning Models: An Easy Guide for Oncologists. IEEE Reviews in Biomedical Engineering, 16 (2023) 192 - 207. doi: 10.1109/RBME.2021.3131358
  
• [2954] C. Sáenz-Royo, F. Chiclana, E. Herrera-Viedma. Functional representation of the intentional bounded rationality of decision-makers: A laboratory to study the decisions a priori. Mathematics, 10(5), 739, Accepted, 2022.. doi: 10.3390/math10050739
  
• [2956] Y. Xu, S. Zhu, X. Liu, J. Huang, E. Herrera-Viedma. Additive consistency exploration of linguistic preference relations with self-confidence. Artificial Intelligence Review volume 56, pages257–285 (2023). doi: 10.1007/s10462-022-10172-x
  
• [2963] R. Fang, H. Liao, Z. Xu, E. Herrera-Viedma. Risk assessment in project management by a graph-theory-based group decision making method with comprehensive linguistic preference information. Economic Research-Ekonomska Istraživanja, (2023) Volume 36, NO. 1, Pages: 86 – 115. doi: 10.1080/1331677X.2022.2070772
  
• [2975] C. Zuheros, E. Martinez-Camara, E. Herrera-Viedma, F. Herrera. Crowd Decision Making: Sparse Representation guided by Sentiment Analysis for leveraging the Wisdom of the Crowd. IEEE Transactions on Systems, Man and Cybernetics:Systems, Volume 53, Issue: 1, Pages 369-379, 2022. Accepted.. doi: 10.1109/TSMC.2022.3180938
  
• [2978] H. Hassani, R. Razavi-Far, M. Saif, F. Chiclana, O. Krejcar, E. Herrera-Viedma. Classical Dynamic Consensus and Opinion Dynamics Models: A Survey of Recent Trends and Methodologies. Information Fusion, Volume 88, December 2022, Pages 22-40, Accepted, 2022.. doi: 10.1016/j.inffus.2022.07.003
  
• [2989] J. Deng, J. Zhan, E. Herrera-Viedma, F. Herrera. Regret theory-based three-way decision method on incomplete multi-scale decision information systems with interval fuzzy numbers. IEEE Transactions on Fuzzy Systems, vol. 31, no. 3, pp. 982-996, March 2023. doi: 10.1109/TFUZZ.2022.3193453
  
• [2990] F. Ji, F. Chiclana, M. Zhou, E. Herrera-Viedma, J. Wu. Ordinal and joint feedback mechanism to support group consensus based on interval-valued number with self-confidence. Information Fusion, Volume 88, December 2022, Pages 202-217, Accepted, 2022.. doi: 10.1016/j.inffus.2022.07.021
  
• [2997] M.S. Santos, P.H. Abreu, N. Japkowicz, A. Fernández, J. Santos. A unifying view of class overlap and imbalance: Key concepts, multi-view panorama, and open avenues for research. Information Fusion 89 (2023) 228-253. doi: 10.1016/j.inffus.2022.08.017
  
• [3000] C. Sáenz-Royo, F. Chiclana, E. Herrera-Viedma. Intentional bounded rationality methodology to assess the quality of decision-making approaches with latent alternative performances. Information Fusion, Volume 89, January 2023, Pages 254-266. doi: 10.1016/j.inffus.2022.08.019
  
• [3007] J.R. Trillo, E. Herrera-Viedma, J.A. Morente-Molinera, F.J. Cabrerizo. A large scale group decision making system based on sentiment analysis cluster. Information Fusion 91 (2023) 633-643. doi: 10.1016/j.inffus.2022.11.009
  
• [3008] X. Xu, Z. Gong, E. Herrera-Viedma, G. Kou, F.J. Cabrerizo. Consensus reaching in group decision making with linear uncertain preferences and asymmetric costs. IEEE Transactions on Systems, Man, and Cybernetics: Systems 53:5 (2023) 2887-2899. doi: 10.1109/TSMC.2022.3220837
  
• [3014] J. Poyatos, D. Molina, A. D. Martínez, J. Del Ser, F. Herrera. EvoPruneDeepTL: An evolutionary pruning model for transfer learning based deep neural networks. Neural Networks, 158 (2023) 59-82. doi: 10.1016/j.neunet.2022.10.011
  
• [3018] Y. Du, Z.S. Chen, J. Yang, J.A. Morente-Molinera, L. Zhang, E. Herrera-Viedma. A Textual Data-Oriented Method for Doctor Selection in Online Health Communities. Sustainability 15, no. 2: 1241. doi: 10.3390/su15021241
  
• [3019] J. Herce-Zelaya, C. Porcel, A. Tejeda-Lorente, J. Bernabé-Moreno, E. Herrera-Viedma. Introducing CSP Dataset: A Dataset Optimized for the Study of the Cold Start Problem in Recommender Systems. Information 14, no. 1: 19. doi: 10.3390/info14010019
  
• [3020] Z. Yan, W. Liu, W. Xing, E. Herrera-Viedma. A Multi-Objective Mission Planning Method for AUV Target Search. Journal of Marine Science and Engineering 11, no. 1: 144. doi: 10.3390/jmse11010144
  
• [3021] A.I. Maghsoodi, A.E. Torkayesh, L.C. Wood, E. Herrera-Viedma, K. Govindan. A machine learning driven multiple criteria decision analysis using LS-SVM feature elimination: Sustainability performance assessment with incomplete data. Engineering Applications of Artificial Intelligence,Volume 119, 2023. doi: 10.1016/j.engappai.2022.105785
  
• [3030] Á. Torres-Martos, M. Bustos-Aibar, A. Ramírez-Mena, S. Cámara-Sánchez, A. Anguita-Ruiz, R. Alcalá, C.M. Aguilera, J. Alcalá-Fdez. Omics Data Preprocessing for Machine Learning: A Case Study in Childhood Obesity. Genes 14:2 (2023) 248. doi: 10.3390/genes14020248
  
• [3032] F. Aghaei, M. Sabokrou, A. Fernandez. Fuzzy Rule-Based Explainer Systems for Deep Neural Networks: From Local Explainability to Global Understanding. IEEE Transactions on Fuzzy Systems 31:9 (2023) 3069-3080. doi: 10.1109/TFUZZ.2023.3243935
  
• [3033] S. Kumar-Das, N. Dey, R. Gonzalez-Crespo, E. Herrera-Viedma. A Non-Linear Multi-Objective Technique for Hybrid Peer-to-Peer Communication. Information Sciences 629 (2023) 413–439. doi: 10.1016/j.ins.2023.01.117
  
• [3038] J. Zhu, X. Ma, Gang Kou, E. Herrera-Viedma, J. Zhan. A three-way consensus model with regret theory under the framework of probabilistic linguistic term sets. Information Fusion, Volume 95, 2023, 250-274.. doi: 10.1016/j.inffus.2023.02.029
  
• [3039] E. Hallaji, R. Razavi-Far, M. Saif, E. Herrera-Viedma. Label noise analysis meets adversarial training: A defense against label poisoning in federated learning. Knowledge-Based Systems,Volume 266, 2023, 110384. doi: 10.1016/j.knosys.2023.110384
  
• [3040] Q. Jia, E. Herrera-Viedma. Pythagorean Fuzzy Sets to Solve Z-Numbers in Decision-Making Model. IEEE Transactions on Fuzzy Systems, vol. 31, no. 3, pp. 890-904, March 2023. doi: 10.1109/TFUZZ.2022.3191359
  
• [3041] S. D'Ambrosi, S. Giannoukakos, M. Antunes-Ferreira, C. Pedraz-Valdunciel, J. W. P. Bracht, N. Potie, A. Gimenez-Capitan, M. Hackenberg, A. Fernandez, M. A. Molina-Vila, R. Rosell, T. Würdinger, D. Koppers-Lalic. Combinatorial Blood Platelets-Derived circRNA and mRNA Signature for Early-Stage Lung Cancer Detection. International Journal of Molecular Sciences 24:5 (2023) 4881:1-4881:17. doi: 10.3390/ijms24054881
  
• [3042] C. Xu, C. Xu, W. Xing, E. Herrera-Viedma. Guided Trajectory Filtering for Challenging Long-range AUV Navigation. IEEE Trans. on Instrumentation and Measurement, 2023.
  
• [3043] C. Biedma-Rdguez, M.J. Gacto, A. Anguita-Ruiz, R. Alcalá, C.M. Aguilera, J. Alcalá-Fdez. Learning positive-negative rule-based fuzzy associative classifiers with a good trade-off between complexity and accuracy. Fuzzy Sets and Systems 465 (2023) 108511. doi: 10.1016/j.fss.2023.03.014
  
• [3047] J.R. Trillo, E. Herrera-Viedma, J.A. Morente-Molinera, F.J. Cabrerizo. A group decision-making method based on the experts' behaviour during the debate. IEEE Transactions on Systems, Man, and Cybernetics: Systems 53:9 (2023) 5796-5808. doi: 10.1109/TSMC.2023.3275056
  
• [3048] Y. Li, E. Herrera-Viedma, I.J. Pérez, M. Barragán-Guzmán, J.A. Morente-Molinera. Z-number-valued rule-based classification system. Applied Soft Computing, 137, 110168..
  
• [3049] A. Velez-Estevez, I.J. Pérez, P. García-Sánchez, J.A. Moral-Muñoz, M.J. Cobo. New trends in bibliometric APIs: A comparative analysis. Information Processing & Management, 60(4), 103385..
  
• [3050] M. Bustos-Aibar, C.M. Aguilera, J. Alcalá-Fdez, F.J. Ruiz-Ojeda, J. Plaza, A. Plaza-Florido, I. Tofe, M. Gil-Campos, M.J. Gacto, A. Anguita-Ruiz. Shared gene expression signatures between visceral adipose and skeletal muscle tissues are associated with cardiometabolic traits in boys with obesity. Computers in Biology and Medicine 163 (2023) 107085. doi: 10.1016/j.compbiomed.2023.107085
  
• [3053] A. Ramírez-Mena, E. Andrés-León, M.J. Alvarez-Cubero, A. Anguita-Ruiz, L.J. Martinez-Gonzalez, J. Alcalá-Fdez. Explainable artificial intelligence to predict and identify prostate cancer tissue by gene expression. Computer Methods and Programs in Biomedicine 240 (2023) 107719. doi: https://doi.org/10.1016/j.cmpb.2023.107719
  
• [3054] M. Arteaga, M.J. Gacto, M. Galende, J. Alcalá-Fdez, R. Alcalá. Enhancing soft computing techniques to actively address imbalanced regression problems. Expert Systems with Applications 234 (2023) 121011. doi: 10.1016/j.eswa.2023.121011
  
• [3055] Q. Ran, X. Chao, F.J. Cabrerizo, E. Herrera-Viedma. Managing overconfidence behaviors from heterogeneous preference relations in linguistic group decision making. IEEE Transactions on Fuzzy Systems 31:7 (2023) 2435-2449. doi: 10.1109/TFUZZ.2022.3226321
  
• [3056] J. Poyatos, D. Molina, Aitor Martínez-Seras, J. Del Ser, F. Herrera. Multiobjective evolutionary pruning of Deep Neural Networks with Transfer Learning for improving their performance and robustness. Applied Soft Computing 147 (2023) 110757 1-12. doi: 10.1016/j.asoc.2023.110757
  
• [3068] I.Sevillano-García, J. Luengo, F. Herrera. REVEL Framework to Measure Local Linear Explanations for Black-Box Models: Deep Learning Image Classification Case Study. International Journal of Intelligent Systems 2023, 1-34. doi: 10.1155/2023/8068569
  
• [3069] Ignacio Aguilera-Martos, A.M. García-Vico, J. Luengo, S. Damas, F.J. Melero, J.J. Valle-Alonso, F. Herrera. TSFEDL: A python library for time series spatio-temporal feature extraction and prediction using deep learning. Neurocomputing 517, 223-228. doi: 10.1016/j.neucom.2022.10.062
  
• [3070] I. Aguilera-Martos, M. García-Bárzana, D. García-Gil, J. Carrasco, D. López, J. Luengo, F. Herrera. Multi-step histogram based outlier scores for unsupervised anomaly detection: ArcelorMittal engineering dataset case of study. Neurocomputing 544, 126228. doi: 10.1016/j.neucom.2023.126228
  
• [3071] D. López, I. Aguilera-Martos, M. García-Bárzana, F. Herrera, D. García-Gil, J. Luengo. Fusing anomaly detection with false positive mitigation methodology for predictive maintenance under multivariate time series. Information Fusion 100, 101957. doi: 10.1016/j.inffus.2023.101957
  
• [3104] Y. Li, E. Herrera-Viedma, G. Kou, J.A. Morente-Molinera. Z-number-valued rule-based decision trees. Information Sciences 643, 119252.
  
• [3105] Y. Li, E. Herrera-Viedma, I.J. Pérez, W. Xing, J.A. Morente-Molinera. The arithmetic of triangular Z-numbers with reduced calculation complexity using an extension of triangular distribution. Information Sciences 647, 119477.
  

2022 (59)

• [2982] M. Toscano, M.J. Cobo, E. Herrera-Viedma. Software solutions for web information systems in digital humanities: review, analysis and comparative study. Profesional De La información, 31:2 (2022). doi: 10.3145/epi.2022.mar.11
  
• [2979] Y. Li, F.J. Cabrerizo, E. Herrera-Viedma, J.A. Morente-Molinera. A modified uncertainty measure of z-numbers. International Journal of Computers Communications & Control 17:4 (2022) 4862. doi: 10.15837/ijccc.2022.4.4862
  
• [2859] H. Lu, Y. Zhu, Q. Lin, T. Wang, Z. Niu, E. Herrera-Viedma. Heterogeneous Knowledge Learning of Predictive Academic Intelligence in Transportation. IEEE Transactions on Intelligent Transportation Systems (Volume: 23, Issue: 4, April 2022) Pages: 3737 – 3755. doi: 10.1109/TITS.2020.3041904
  
• [2870] G. Beliakov, F.J. Cabrerizo, E. Herrera-Viedma, J.-Z. Wu. Random generation of k-interactive capacities. Fuzzy Sets and Systems 430 (2022) 48-55. doi: 10.1016/j.fss.2020.12.010
  
• [2876] F. Aghaeipoor, M. M. Javidi, A. Fernandez. IFC-BD: An Interpretable Fuzzy Classifier for Boosting Explainable Artificial Intelligence in Big Data. IEEE Transactions on Fuzzy Systems 30:3 (2021) 830-840. doi: 10.1109/TFUZZ.2021.3049911
  
• [2888] C-C Li, Y. Dong, F. Chiclana, E. Herrera-Viedma. Consistency-driven methodology to manage incomplete linguistic preference relation: A perspective based on personalized individual semantics. IEEE Transactions on Cybernetics (Volume: 52, Issue: 7, July 2022) Pages: 6170 – 6180. doi: 10.1109/TCYB.2021.3072147
  
• [2890] Q. Sun, J. Wu, F. Chiclana, H. Fujita, E. Herrera-Viedma. A dynamic feedback mechanism with attitudinal consensus threshold for minimum adjustment cost in group decision making. IEEE Transactions on Fuzzy Systems (Volume: 30, Issue: 5, May 2022) Pages: 1287 - 1301. doi: 10.1109/TFUZZ.2021.3057705
  
• [2891] J.A. Morente-Molinera, Y. Wang, Z. -W. Gong, A. Morfeq, R. Al-Hmouz, E. Herrera-Viedma. Reducing Criteria in Multicriteria Group Decision-Making Methods Using Hierarchical Clustering Methods and Fuzzy Ontologies. IEEE Transactions on Fuzzy Systems ( Volume: 30, Issue: 6, June 2022) Pages: 1585 – 1598. doi: 10.1109/TFUZZ.2021.3062145
  
• [2893] H. Zhang, F. Wang, Y. Dong, F. Chiclana, E. Herrera-Viedma. Social trust-driven consensus reaching model with a minimum adjustment feedback mechanism considering assessments-modifications willingness. IEEE Transactions on Fuzzy Systems (Volume: 30, Issue: 6, June 2022) Pages: 2019 – 2031. doi: 10.1109/TFUZZ.2021.3073251
  
• [2896] J. Wu, S. Wang, F. Chiclana, E. Herrera-Viedma. Two-fold Personalized Feedback Mechanism for Social Network Consensus by Uninorm Interval Trust Propagation. IEEE Transactions on Cybernetics, ( Volume: 52, Issue: 10, October 2022) Pages: 11081 – 11092. doi: 10.1109/TCYB.2021.3076420
  
• [2897] A. Yazidi, M. Ivanovska, F. M. Zennaro, P. G. Lind, E. Herrera-Viedma. A new decision making model based on rank centrality for GDM with fuzzy preference relations. European Journal of Operational Research, 297:3 (2022) 1030-1041.
  
• [2917] X. Ma, Z. Gong, G. Wei, E. Herrera-Viedma. New Consensus Model Based on TrustInteractive Weights for Intuitionistic Group Decision Making in Social Networks. IEEE Transactions on Cybernetics ( Volume: 52, Issue: 12, December 2022) Pages: 13106 – 13119. doi: 10.1109/TCYB.2021.3100849
  
• [2923] Q. Zha, Y. Don, F. Chiclana, E. Herrera-Viedma. Consensus Reaching in Multiple Attribute Group Decision Making: A Multi-Stage Optimization Feedback Mechanism with Individual Bounded Confidences. IEEE Transactions on Fuzzy Systems ( Volume: 30, Issue: 8, Pages: 3333 – 3346, August 2022). doi: 10.1109/TFUZZ.2021.3113571
  
• [2932] Y. Xu, W. Dai, J. Huang, M. Li, E. Herrera-Viedma. Some models to manage additive consistency and derive priority weights from hesitant fuzzy preference relations. Information Sciences 586 (2022) 450-467. doi: 10.1016/j.ins.2021.12.002
  
• [2933] M. Zhou, M. Hu, Y-W. Chen, B-Y. Cheng, J. Wu, E. Herrera-Viedma. Towards achieving consistent opinion fusion in group decision making with complete distributed preference relations. Knowledge-Based Systems, Volume 236, 2022. doi: 10.1016/j.knosys.2021.107740
  
• [2934] J-W. Zhang, F. Liu, H-Ni. Tu, E. Herrera-Viedma. A decision-making model with sequential incomplete additive pairwise comparisons. Knowledge-Based Systems 236 (2022) 107766. doi: 10.1016/j.knosys.2021.107766
  
• [2939] S. Maldonado, C. Vairetti, A. Fernandez, F. Herrera. FW-SMOTE: a feature-weighted oversampling approach for imbalanced classification. Pattern Recognition, 124, 108511:1-16 (2022). doi: 10.1016/j.patcog.2021.108511
  
• [2941] S. Wang, J. Wu, F. Chiclana, Q. Sun, E. Herrera-Viedma. Two stage feedback mechanisms with different power structures for consensus in large-scale group decision-making. IEEE Transactions on Fuzzy Systems ( Volume: 30, Issue: 10, October 2022) pp. 4177 – 4189. doi: 10.1109/TFUZZ.2022.3144536
  
• [2942] C- Pedraz-Valdunciel, S. Giannoukakos, N. Potie, A. Gimenez-Capitan,C-Y Huang,M. Hackenberg, A. Fernandez, J. Bracht, M. Filipska, E. Aldeguer, S. Rodriguez, T. G. Bivona, S. Warren, C. Aguado, M. Ito, A. Aguilar-Hernandez, M.A. Molina-Vila. R. Rosell. Digital multiplexed analysis of circular RNAs in FFPE and fresh non-small cell lung cancer specimens. Molecular Oncology 16:12 (2022) 2367-2383. doi: 10.1002/1878-0261.13182
  
• [2943] M.S. Santos, P.H. Abreu, A. Fernández, J. Luengo, J. Santos. The impact of heterogeneous distance functions on missing data imputation and classification performance. Engineering Applications of Artificial Intelligence, 111 (2022) 104791. doi: 10.1016/j.engappai.2022.104791
  
• [2944] A. Yazidi, M. Ivanovska, F.M. Zennaro, P.G. Lind, E. Herrera-Viedma. A new decision making model based on Rank Centrality for GDM with fuzzy preference relations. European Journal of Operational Research 297:3 (2022) 1030-1041. doi: 10.1016/j.ejor.2021.05.030
  
• [2945] I. Bueno, R.A. Carrasco, R. Ureña, E. Herrera-Viedma. A business context aware decision-making approach for selecting the most appropriate sentiment analysis technique in e-marketing situations. Information Sciences 589 (2022) 300-320. doi: 10.1016/j.ins.2021.12.080
  
• [2946] A. Yazidi, M.A. Pinto-Orellana, H. Hammer, P. Mirtaheri, E. Herrera-Viedma. Solving Sensor Identification Problem Without Knowledge of the Ground Truth Using Replicator Dynamics. IEEE Transactions on Cybernetics 52:1 (2022) 16-24. doi: 10.1109/TCYB.2019.2958627
  
• [2953] X. Sun, S. Ge, X. Wang, H. Lu, E. Herrera-Viedma. A Bibliometric Analysis of IEEE T-ITS Literature Between 2010 and 2019. IEEE Transactions on Intelligent Transportation Systems, Volume 23, Issue: 10, Pages 17157-17166, 2022, Accepted.. doi: 10.1109/TITS.2022.3154098
  
• [2955] M. Pérez-Pons, J. Parra-Dominguez, G. Hernández, E. Herrera-Viedma, J. Corchado. Evaluation metrics and dimensional reduction for binary classification algorithms: A case study on bankruptcy prediction. The Knowledge Engineering Review, 37, E1.. doi: 10.1017/S026988892100014X
  
• [2957] D. Molina, J. Poyatos, E. Osaba, J. Del Ser, F. Herrera. Nature-And Bio-Inspired Optimization: The Good, The Bad, The Ugly And The Hopeful. Dyna, 97:2 (2022) 114-117. doi: 10.6036/10331
  
• [2958] X. Liu, N. Wang, D. Molina, F. Herrera. A least square support vector machine approach based on bvRNA-GA for modeling photovoltaic systems. Applied Soft Computing, 117 (2022) 108357. doi: 10.1016/j.asoc.2021.108357
  
• [2959] M.S. Santos, P.H. Abreu, N. Japkowicz, A. Fernández, C. Soares, S. Wilk, J. Santos. On the joint-efect of class imbalance and overlap: a critical review. Artifcial Intelligence Review 55 (2022) 6207–6275. doi: 10.1007/s10462-022-10150-3
  
• [2961] A. Segura-Delgado, A. Anguita-Ruiz, R. Alcalá, J. Alcalá-Fdez. Mining high average-utility sequential rules to identify high-utility gene expression sequences in longitudinal human studies. Expert Systems with Applications 193 (2022) 116411. doi: 10.1016/j.eswa.2021.116411
  
• [2962] H. Liang, G. Kou, Y. Dong, F. Chiclana, E. Herrera-Viedma. Consensus Reaching with Minimum Cost of Informed Individuals and Time Constraints in Large-scale Group Decision Making. IEEE Transactions on Fuzzy Systems ( Volume: 30, Issue: 11, Pages: 4991 - 5004, November 2022). doi: 10.1109/TFUZZ.2022.3165373
  
• [2969] Y. Xu, Z. Gong, G. Wei, W. Guo, E. Herrera-Viedma. Information consistent degree-based clustering method for large-scale group decision-making with linear uncertainty distributions information. Int. J. of Intelligent Systems, 2022 37:3394-3439. doi: 10.1002/int.22695
  
• [2970] X. Zhang, J. Su, E. Herrera-Viedma. A decision support model for estimating participation-oriented designs of crowdsourcing platforms based on quality function deployment. Expert Systems with Applications, Volume 202, (2022). doi: 10.1016/j.eswa.2022.117308
  
• [2971] J. Deng, J. Zhan, Z. Xu, E. Herrera-Viedma. Regret-theoretic multi-attribute decision-making model using three-way framework in multi-scale information systems. IEEE Transactions on Cybernetics, Accepted, 2022.. doi: 10.1109/TCYB.2022.3173374
  
• [2974] J. Marques Oliveira, B. Sicardy, ..., S. Alonso, et al.. Constraints on the structure and seasonal variations of Triton's atmosphere from the 5 October 2017 stellar occultation and previous observations. Astronomy and Astrophysics 659 (2022) A136. doi: 10.1051/0004-6361/202141443
  
• [2976] J.R. Trillo, F.J. Cabrerizo, F. Chiclana, M.A. Martínez, F. Mata, E. Herrera-Viedma. Theorem verification of the quantifier-guided dominance degree with the mean operator for additive preference relations. Mathematics 2022, 10(12), 2035. doi: 10.3390/math10122035
  
• [2977] X. Chao, G. Kou, Y. Peng. A. Fernández. An Efficiency Curve for Evaluating Imbalanced Classifiers Considering Intrinsic Data Characteristics: Experimental Analysis. Information Sciences 608 (2022) 1131-1156. doi: 10.1016/j.ins.2022.06.045
  
• [2983] A. Martínez-Martínez, J.Gl Cegarra-Navarro, M.J. Cobo, T. de Valon. Impacts and Implications for Advancing in Environmental Knowledge in Hospitality Industry in COVID Society: a Bibliometric Analysis. Journal of the Knowledge Economy (2022). doi: 10.1007/s13132-022-00910-5
  
• [2985] J. Padilla-Cabello, A. Santisteban-Espejo, R. Heradio, M.J. Cobo, M.A. Martin-Piedra, J.A. Moral-Muñoz. Methods for identifying biomedical translation: a systematic review. American Journal of Translational Research, 14:4, pp. 2697-2708 (2022).
  
• [2986] A. Santisteban-Espejo, M.A. Martin-Piedra, A. Campos, J. Moran-Sanchez, M.J. Cobo, A.I. Pacheco-Serrano, J.A. Moral-Muñoz. Information and Scientific Impact of Advanced Therapies in the Age of Mass Media: Altmetrics-Based Analysis of Tissue Engineering. Journal of Medical Internet Research, 23:11, e25394 (2022). doi: 10.2196/25394
  
• [2988] M. Zhou, Z.-X. Guan, Y.-W. Chen, Z.-P. Zhou, J. Wu, E. Herrera-Viedma. Consistency and consensus reaching process for group decision making based on complete interval distributed preference relations under social network analysis. Information Fusion, Volume 88, Pages 126-145, Accepted, 2022.. doi: 10.1016/j.inffus.2022.07.015
  
• [2991] W. Wang, J. Zhan, E. Herrera-Viedma. A three-way decision approach with a probability dominance relation based on prospect theory for incomplete information systems. Information Sciences, Volume 611, September 2022, Pages 199-224. doi: 10.1016/j.ins.2022.08.065
  
• [2993] A. Velez-Estevez, P. Garcia-Sanchez, J.A. Moral-Muñoz, M.J. Cobo. Why do papers from international collaborations get more citations? A bibliometric analysis of Library and Information Science papers. Scientometrics (2022). doi: 10.1007/s11192-022-04486-4
  
• [2994] V. Duarte-Martínez, M.J. Cobo, A.G. López-Herrera. Uncovering patterns in the supervision of Spanish theses: a comprehensive analysis. Journal of Informetrics, 16:3, pp. 101319 (2022). doi: 10.1016/j.joi.2022.101319
  
• [2998] C. Biedma-Rdguez, M.J. Gacto, A. Anguita-Ruiz, J. Alcalá-Fdez, R. Alcalá. Transparent but Accurate Evolutionary Regression Combining New Linguistic Fuzzy Grammar and a Novel Interpretable Linear Extension. International Journal of Fuzzy Systems 24 (2022) 3082–3103. doi: 10.1007/s40815-022-01324-w
  
• [2999] R. Abolghasemi, R. Khadka, P. G. Lind, P. Engelstad, E. Herrera-Viedma, A. Yazidi. Predicting missing pairwise preferences from similarity features in group decision making. Knowledge-Based Systems, Volume 256, Accepted, 2022. doi: 10.1016/j.knosys.2022.109860
  
• [3001] W. Wang, J. Zhan, C. Zhang, E. Herrera-Viedma, G. Kou. A regret-theory-based three-way decision method with a priori probability tolerance dominance relation in fuzzy incomplete information systems. Information Fusion, Volume 89, January 2023, Pages 382-396, Accepted, 2022. doi: 10.1016/j.inffus.2022.08.027
  
• [3002] Y. Du, D. Lio, J.A. Morente-Molinera, E. Herrera-Viedma. A data-driven method for user satisfaction evaluation of smart and connected products. Expert Systems with Applications, Volume 210. Accepted, 2022. doi: 10.1016/j.eswa.2022.118392
  
• [3003] H. Zhang, S. Liu, Y. Dong, F. Chiclana, E. Herrera-Viedma. A minimum cost consensus-based failure mode and effect analysis framework considering experts’ limited compromise and tolerance behaviors. IEEE Transactions on Cybernetics, Accepted, 2022. doi: 10.1109/TCYB.2022.3212093
  
• [3004] A. Seal, R. Bajpai, M. Karnati, J. Agnihotri, A. Yazidi, E. Herrera-Viedma, O. Krejcar. Benchmarks for Machine Learning in Depression Discrimination using Electroencephalography Signals. Applied Intelligence, Accepted, 2022. doi: 10.1007/s10489-022-04159-y
  
• [3005] Q. Jia, J. Hu and E. Herrera-Viedma. A Novel Solution for Z-numbers Based on Complex Fuzzy Sets and Its Application in Decision-making System. IEEE Transactions on Fuzzy Systems, 30:10, (2022) pp. 4102-4114. doi: 10.1109/TFUZZ.2021.3138649
  
• [3006] H. Hassani, R. Razavi-Far, M. Saif, E. Herrera-Viedma. Reinforcement Learning-Based Feedback and Weight-Adjustment Mechanisms for Consensus Reaching in Group Decision Making. IEEE Transactions on Systems, Man, and Cybernetics: Systems. doi: 10.1109/TSMC.2022.3214221
  
• [3022] Q.D. Nguyet, A. Selamat, O. Krejcar, E. Herrera-Viedma, H. Fujita. Deep Learning for Phishing Detection: Taxonomy, Current Challenges and Future Directions. IEEE Access, 2022, Volume 10, Pages 36429 – 36463. doi: 10.1109/ACCESS.2022.3151903
  
• [3023] H. Hassani, R. Razavi-Far, M. Saif, E. Herrera-Viedma. Consensus-Based Decision Support Model and Fusion Architecture for Dynamic Decision Making. Information Sciences, Volume 597, Pages 86-104, 2022. doi: 10.1016/j.ins.2022.03.040
  
• [3024] R. Abolghasemi, P. Engelstad, E. Herrera-Viedma, A. Yazidi. A Personality-Aware Group Recommendation System Based on Pairwise Preferences. Information Sciences, Volume 595, May 2022, Pages 1-17. doi: 10.1016/j.ins.2022.02.033
  
• [3026] M.E. Perez-Pons, J. Parra-Dominguez, S. Omatu, E. Herrera-Viedma, J.M. Corchado. Machine Learning and Traditional Econometric Models: A Systematic Mapping Study. J of AI and Soft Computing Research, volumen 12, No. 2, pp. 79 – 100, (2022). doi: 10.2478/jaiscr-2022-0006
  
• [3027] Z. Troya, R. Esteban, E. Herrera-Viedma, A. Peña-García. People’s perception of experimental installations for sustainable energy: the case of IFMIF-DONES. Sustainability 2022, 14(2), 899. doi: 10.3390/su14020899
  
• [3045] Pedraz-Valdunciel, C; Giannoukakos, S; Gimenez-Capitan, A; Fortunato, D; Filipska, M; Bertran-Alamillo, J; Bracht, JWP; Drozdowskyj, A; Valarezo, J; Zarovni, N; A. Fernandez; Hackenberg, M; Aguilar-Hernandez, A; Molina-Vila, MA; Rosell, R.. Multiplex Analysis of CircRNAs from Plasma Extracellular Vesicle-Enriched Samples for the Detection of Early-Stage Non-Small Cell Lung Cancer. Pharmaceutics 14:10 (2022) 2034:1-2034:10. doi: 10.3390/pharmaceutics14102034
  
• [3075] G. González-Almagro, J.L. Suárez, J. Luengo, J.R. Cano, S. García. 3SHACC: Three stages hybrid agglomerative constrained clustering. Neurocomputing 490: 441-461 (2022). doi: 10.1016/j.neucom.2021.12.018
  
• [3076] J. Luengo, R. Moreno, I. Sevillano-García, D. Charte, A. Peláez-Vegas, M. Fernández-Moreno, P. Mesejo, F. Herrera. A tutorial on the segmentation of metallographic images: Taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges. Information Fusion 78, 232-253. doi: 10.1016/j.inffus.2021.09.018
  

2021 (70)

• [2884] W. Guo, Z. Gong, E. Herrera-Viedma, Q. Li. Priority weights acquisition of linear uncertain preference relations and its application in the ranking of online shopping platforms. ASOC, 105 (2021) 107292..
  
• [2883] G. Kou, Y. Peng, Xiangrui Chao, E. Herrera-Viedma, F. E. Alsaadi. A geometrical method for consensus building in GDM with incomplete heterogeneous preference information. ASOC 105 (2021) 107224. doi: 10.1016/j.asoc.2021.107224
  
• [2885] P. García-Sánchez, A. Velez-Estevez, J.J. Merelo, M.J. Cobo. The Simpsons did it: Exploring the film trope space and its large scale structure. PLOS ONE 16:3: e0248881 (2021). doi: 10.1371/journal.pone.0248881
  
• [2886] G. Fenza, M. Gallo, V. Loia, F. Orciuoli, E. Herrera-Viedma. Data set quality in Machine Learning: Consistency measure based on Group Decision Making. ASOC 106 (2021) 107366. doi: 10.1016/j.asoc.2021.107366
  
• [2134] Y. Dong, Z. Ding, F. Chiclana, E. Herrera-Viedma. Dynamics of public opinions in an online and offline social network. IEEE Transactions on Big Data 7:4 (2021) 610-618. doi: 10.1109/TBDATA.2017.2676810
  
• [2693] Y. Xu, M. Li, F.J. Cabrerizo, F. Chiclana, E. Herrera-Viedma. Algorithms to detect and rectify multiplicative and ordinal inconsistencies of fuzzy preference relations. IEEE Transactions on Systems, Man, and Cybernetics: Systems 51:6 (2021) 3498-3511. doi: 10.1109/TSMC.2019.2931536
  
• [2895] E. Osaba, E. Villar-Rodriguez, J. Del Ser, A. J. Nebro, D. Molina, A. La Torre, P.N. Suganthan, C.A. Coello, F. Herrera. A Tutorial on the Design, Experimentation and Application of Metaheuristic Algorithms to Real-World Optimization Problems. Swarm and Evolutionary Computation.64 (2021), 100888. doi: 10.1016/j.swevo.2021.100888
  
• [2731] A. Seal, A. Karlekar, O. Krejcar, E. Herrera-Viedma. Performance and convergence analysis of modified c-means using Jeffreys-divergence for clustering. IJIMAI, 7:2 (2021) 141-147. doi: 10.9781/ijimai.2021.04.009
  
• [2748] H. Seiti, M. Fathi, A. Hafezalkoto, E. Herrera-Viedma, I. A. Hameed. Developing the modified R-numbers for risk-based fuzzy information fusion and its application to failure modes, effects, and system resilience analysis (FMESRA). ISA Transactions 113 (2021) 9-27. doi: 10.1016/j.isatra.2020.01.015
  
• [2755] M. Tang, H. Liao, E. Herrera-Viedma, C.L. Philip Chen, W. Pedrycz. A Dynamic Adaptive Subgroup-to-Subgroup Compatibility Based Conflict Detection and Resolution Model for Fuzzy Multi-Criteria Large-Scale Group Decision Making. IEEE Transactions on Cybernetics 51:10 (2021) 4784-4795. doi: 10.1109/TCYB.2020.2974924
  
• [2764] S. Laengle, V. Lobos, J.M. Merigó, E. Herrera-Viedma, M.J. Cobo, B. De Baets. Forty years of Fuzzy Sets and Systems: A bibliometric analysis. Fuzzy Set and Systems 402 (2021) 155-183. doi: 10.1016/j.fss.2020.03.012
  
• [2768] J. Wu, M. Cao, F. Chiclana, Y. Dong, E. Herrera-Viedma. An optimal feedback model to prevent manipulation behaviour in consensus under social network group decision making. IEEE Transactions on Fuzzy Systems 29:7 (2021) 1750-1763. doi: 10.1109/TFUZZ.2020.2985331
  
• [2775] S. Laengle, V. Lobos, J.M.Merigó, E. Herrera-Viedma, M.J. Cobo, B. De Baets. Forty years of Fuzzy Sets and Systems: A bibliometric analysis. Fuzzy Sets and Systems, 402 (2021) 155–183. doi: 10.1016/j.fss.2020.03.012
  
• [2807] X. Chao, G. Kou, Yi Peng, Fawaz E. Alsaadi, E. Herrera-Viedma. Large-Scale Group Decision-making with Non-cooperative Behaviors and Heterogeneous Preferences: An application in Financial Inclusion. European Journal of Operational Research, Volume 288, Issue 1, 1 January 2021, Pages 271-293..
  
• [2832] N. Garcia-Buendia, J. Moyano-Fuentes, J.M. Maqueira, M.J. Cobo. 22 years of Lean Supply Chain Management: a science mapping-based bibliometric analysis. International Journal of Production Research, 59:6, pp. 1901-1921 (2021). doi: 10.1080/00207543.2020.1794076
  
• [2835] Z. Gong, X. Xu, W. Guo, E. Herrera-Viedma, F.J. Cabrerizo. Minimum cost consensus modeling under various linear uncertain-constrained scenarios. Information Fusion 66 (2021) 1-17. doi: 10.1016/j.inffus.2020.08.015
  
• [2836] E. León-Castro, L.F. Espinoza-Audelo, J.M. Merigó, E. Herrera-Viedma, F. Herrera. Measuring volatility based on ordered weighted average operators: Agricultural products prices case of use. Fuzzy Sets and Systems 422 (2021) 161-176. doi: 10.1016/j.fss.2020.08.006
  
• [2840] Y. Lu, Y. Xu, E. Herrera-Viedma, Y. Han. Consensus of large-scale group decision making in social network: the minimum cost model based on robust optimization. Information Sciences, Vol. 547, 2021, 910-930..
  
• [2851] C. Jebari, E. Herrera-Viedma, M.J. Cobo. The use of citation context to detect the evolution of research topics: a large-scale analysis. Scientometrics, 126, pp. 2971–2989 (2021). doi: 10.1007/s11192-020-03858-y
  
• [2853] A. D. Martinez, J. del Ser, E. Villa-Rodriguez, E. Osaka, J. Poyatos, S. Tabik, D. Molina, F. Herrera. Lights and Shadows in Evolutionary Deep Learning: Taxonomy, Critical Methodological Analysis, Cases of Study, Learned Lessons,Recommendations and Challenges. Information Fusion 67 (2021) 161-194. doi: 10.1016/j.inffus.2020.10.014
  
• [2854] M.S. Cao, J. Wu, F. Chiclana, R. Ureña, E. Herrera-Viedma. A Personalized Consensus Feedback Mechanism Based on Maximum Harmony Degree. IEEE Transactions on Systems, Man and Cybernetics: Systems 51:10 (2021) 6134-6146. doi: 10.1109/TSMC.2019.2960052
  
• [2860] X. Tan, J. Zhu, F.J. Cabrerizo, E. Herrera-Viedma. A cyclic dynamic trust-based consensus model for large-scale group decision making with probabilistic linguistic information. Applied Soft Computing 100 (2021) 106937. doi: 10.1016/j.asoc.2020.106937
  
• [2880] H. Zhang, Y. Dong, J. Xiao, F. Chiclana, E. Herrera-Viedma. Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts. Reliability Engineering & System Safety 208 (2021) 107425. doi: 10.1016/j.ress.2020.107425
  
• [2878] C. Zhang, W. Su, S. Zeng, T. Balezentis, E. Herrera-Viedma. A Two-stage subgroup Decision-making method for processing Large-scale information. Expert Systems with Applications 171 (2021) 114586. doi: 10.1016/j.eswa.2021.114586
  
• [2879] L. Li , Q. Chen , X. Jia. E. Herrera-Viedma. Co-patents’ commercialization: evidence from China. Economic Research-Ekonomska Istraživanja 34:1 (2021) 1709-1726. doi: 10.1080/1331677X.2020.1845761
  
• [2882] A. Kirimtat, O. Krejcar, M. . Tasgetiren, E. Herrera-Viedma. Multi-performance based computational model for the cuboid open traveling salesman problem in a smart floating city. Building and Environment, Volume 196, June 2021, 107721.. doi: 10.1016/j.buildenv.2021.10772
  
• [2871] I. Bueno, R.A. Carrasco, C. Porcel, G. Kou, E. Herrera-Viedma. A linguistic multi-criteria decision making methodology for the evaluation of tourist services considering customer opinion value. Applied Soft Computing 101 (2021) 107045. doi: 10.1016/j.asoc.2020.107045
  
• [2872] X. Gou, Z. Xu, W. Zhou, E. Herrera-Viedma. The Risk Assessment of Construction Project Investment based on Prospect Theory with Linguistic Preference Orderings. Economic Research-Ekonomska Istraživanja 34:1 (2021) 709-731. doi: 10.1080/1331677X.2020.1868324
  
• [2873] E. Herrera-Viedma, I. Palomares, C.-C. Li, F.J. Cabrerizo, Y.C. Dong, F. Chiclana, F. Herrera. Revisiting fuzzy and linguistic decision making: Scenarios and challenges for making wiser decisions in a better way. IEEE Transactions on Systems, Man, and Cybernetics: Systems 51:1 (2021) 191-208. doi: 10.1109/TSMC.2020.3043016
  
• [2874] E. Tunstel, M.J. Cobo, E. Herrera-Viedma, I.J. Rudas, D. Filev, L. Trajkovic, C.L.P. Chen, W. Pedrycz, M.H. Smith, R. Kozma. Systems Science and Engineering Research in the Context of Systems, Man, and Cybernetics: Recollection, Trends, and Future Directions. IEEE Trans. Syst. Man and Cyb: Systems 51:1 (2021) 5-21. doi: 10.1109/TSMC.2020.3043192
  
• [2875] W. Guo, Z. Gong, X. Xu, O. Krejcar, E. Herrera-Viedma. Linear uncertain extensions of the minimum cost consensus model based on uncertain distance and consensus utility. Information Fusion 70 (2021) 12–26. doi: 10.1016/j.inffus.2020.12.002
  
• [2881] A. Seal, R. Bajpai, J. Agnihotri, A. Yazidi, E. Herrera-Viedma, O. Krejcar. DeprNet: A Deep Convolution Neural Networks Framework for Detecting Depression using EEG. IEEE Transactions on Instrumentation and Measurement vol. 70, pp. 1-13, 2021, Art no. 2505413,. doi: 10.1109/TIM.2021.3053999
  
• [2887] K. K. Sharma, A. Seal, E. Herrera-Viedma, O. Krejcar. An Enhanced Spectral Clustering Algorithm with S-Distance. Symmetry. 2021; 13(4):596.. doi: 10.3390/sym13040596
  
• [2892] W. Guo, Z. Gong, X. Xu and E. Herrera-Viedma. Additive and Multiplicative Consistency Modeling for Incomplete Linear Uncertain Preference Relations and Its Weight Acquisition. IEEE Transactions on Fuzzy Systems, vol. 29, no. 4, pp. 805-819, April 2021. doi: 10.1109/TFUZZ.2020.2965909
  
• [2894] B. Farhadinia, H. Liao, E. Herrera-Viedma. A modified class of correlation coefficients of hesitant fuzzy information. Soft Comput 25, 7009–7028 (2021). doi: 10.1007/s00500-021-05629-0
  
• [2898] J.D. Pascual, D. Charte, M. Andrés, A. Fernández, F. Herrera. Revisiting data complexity metrics based onmorphology for overlap and imbalance: snapshot, new overlap number of balls metrics and singular problems prospect. Knowledge and Information Systems 63 (2021) 1961–1989. doi: 10.1007/s10115-021-01577-1
  
• [2899] S. Alonso, R. Montes, D. Molina, I. Palomares, E. Martínez-Cámara, M. Chiachio, J. Chiachio, F.J. Melero, P. García-Moral, B. Fernández, C. Moral, R. Marchena, J. Pérez de Vargas, F. Herrera. Article Ordering Artificial Intelligence Based Recommendations to Tackle the SDGs with a Decision-Making Model Based on Surveys. Sustainability 2021, 13(11), 6038. doi: 10.3390/su13116038
  
• [2900] C.C. Li, H. Liang, Y. Dong, F. Chiclana, E. Herrera-Viedma. Consistency improvement with a feedback recommendation in personalized linguistic group decision making. IEEE Transactions on Cybernetics, Volume 52, Issue: 10, Pages 10052-10063, Accepted, 2021.. doi: 10.1109/TCYB.2021.3085760
  
• [2903] A. Lamas, S. Tabik, P. Cruz, R. Montes, A. Martínez-Sevilla, T. Cruz, F. Herrera. MonuMAI: Dataset, deep learning pipeline and citizen science based app for monumental heritage taxonomy and classification. Neurocomputing 420 (2021)266-280. doi: j.neucom.2020.09.041
  
• [2904] X. Xu, Z. Gong, W. Guo, Z. Wu, E. Herrera-Viedma, F.J. Cabrerizo. Optimization consensus modeling of a closed-loop carbon quota trading mechanism regarding revenue and fairness. Computers & Industrial Engineering 161 (2021) 107611. doi: 10.1016/j.cie.2021.107611
  
• [2905] J.A. Morente-Molinera, G.Kou, K. Samuylov, F.J. Cabrerizo, E. Herrera-Viedma. Using argumentation in expert's debate to analyze multi-criteria group decision making method results. Information Sciences 573 (2021) 433-452. doi: 10.1016/j.ins.2021.05.086
  
• [2906] I. Palomares, E. Martínez-Cámara, R. Montes, P. García-Moral, M. Chiachio, J. Chiachio, S. Alonso, F.J. Melero, D. Molina, B. Fernández, C. Moral, R. Marchena, J.P. de Vargas, F. Herrera. A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects. Applied Intelligence, (2021) 51, 6497-6527. doi: 10.1007/s10489-021-02264-y
  
• [2907] J.R. López-Robles, M.J. Cobo, M. Gutiérrez-Salcedo, M.A. Martínez-Sánchez, N.K. Gamboa-Rosales, E. Herrera-Viedma. 30th Anniversary of Applied Intelligence: A combination of bibliometrics and thematic analysis using SciMAT. Applied Intelligence, 51 (2021) 6547–6568. doi: 10.1007/s10489-021-02584-z
  
• [2908] S. Dianah A. Bujang, A. Selamat, R Ibrahim, O. Krejcar, E. Herrera-Viedma, H. Fujita, A. Ghani. Multiclass Prediction Model for Student Grade Prediction using Machine Learning. IEEE Access 9 (2021) 95608-95621. doi: 10.1109/ACCESS.2021.3093563
  
• [2909] T. Person, I. Ruiz-Rube, J.M. Mota, M.J. Cobo, A. Tselykh, J.M. Dodero. A comprehensive framework to reinforce evidence synthesis features in cloud-based systematic review tools. Applied Science, 11:2, 5527. doi: 10.3390/app11125527
  
• [2910] M.K. Sott, L.B. Furstenau, L.M. Kipper, Y.P. Reckziegel-Rodrigues, J.R. López-Robles, F.D Giraldo, M.J. Cobo. Process modeling for smart factories: using science mapping to understand the strategic themes, main challenges and future trends. Business Process Management Journal, 27:5 (2021) 1391-1417. doi: 10.1108/BPMJ-05-2020-0181
  
• [2911] P. Sánchez-Núñez, M.J. Cobo, G. Vaccaro, J.I. Peláez, E. Herrera-Viedma. Citation classics in consumer neuroscience, neuromarketing and neuroaesthetics: Identification and conceptual analysis. Brain Sciences, 11:5, 548 (2021). doi: 10.3390/brainsci11050548
  
• [2912] L.B Furstenaua, M.K. Sott, A.J. Ouriques-Homrich, L.M. Kipper, M.S. Dohan, J.R. López-Robles, M.J. Cobo, G.L. Tortorella. An overview of 42 years of lean production: applying bibliometric analysis to investigate strategic themes and scientific evolution structure. Technology Analysis & Strategic Management, 33:9 (2021), 1068–1087. doi: 10.1080/09537325.2020.1865530
  
• [2916] T. Kumarasinghe, O. Krejcar, A. Selamat, N. M. Dawi, E. Herrera-Viedma, R. Frischer, H. Namazi. Complexity-based evaluation of the correlation between heart and brain responses to music. Fractals 29:6 (2021) 2150238. doi: 10.1142/S0218348X21502388
  
• [2918] Y. Xu, M. Li, F. Chiclana, E. Herrera-Viedma. Multiplicative Consistency Ascertaining, Inconsistency Repairing and Weights Derivation of Hesitant Multiplicative Preference Relations. IEEE Trans. Syst. Man and Cyb: Systems, 52 (11), 6806-6821, 2021.. doi: 10.1109/TSMC.2021.3099862
  
• [2920] A. LaTorre, D. Molina, E. Osaba, J. Poyatos, J. Del Ser, F. Herrera. A prescription of methodological guidelines for comparing bio-inspired optimization algorithms. Swarm and Evolutionary Computation, 67 (2021) 100973. doi: 10.1016/j.swevo.2021.100973
  
• [2921] J.A. Fdez-Sánchez, J.D. Pascual-Triana, A. Fernandez, F. Herrera. Learning interpretable multi-class models by means of hierarchical decomposition: Threshold Control for Nested Dichotomies. Neurocomputing 463 (2021) 514-524. doi: 10.1016/j.neucom.2021.07.097
  
• [2922] M.J. Basgall, M. Naiouf, A. Fernandez. FDR2-BD: A Fast Data Reduction Recommendation Tool for Tabular Big Data Classification Problems. Electronics 10:15 (2021) 1757. doi: 10.3390/electronics10151757
  
• [2924] M. Chen, Z. Guo, Y. Dong, F. Chiclana, E. Herrera-Viedma. Citations optimal growth path: A tool to analyze sensitivity to citations of h-like indexes. Journal of Informetrics 15:4 (2021) 101215. doi: 10.1016/j.joi.2021.101215
  
• [2929] A. Anguita-Ruiz; M. Bustos-Aibar; J. Plaza-Díaz; A. Mendez-Gutierrez; J. Alcalá-Fdez; C.M. Aguilera; F.J. Ruiz-Ojeda. Omics Approaches in Adipose Tissue and Skeletal Muscle Addressing the Role of Extracellular Matrix in Obesity and Metabolic Dysfunction. International Journal of Molecular Sciences 22:5 (2021) 2756. doi: 10.3390/ijms22052756
  
• [2930] M. Mohamad, A. Selamat, O. Krejcar, R. Gonzalez-Crespo, E. Herrera-Viedma, H. Fujita. Enhancing Big Data Feature Selection Using a Hybrid Correlation-Based Feature Selection. Electronics 2021, 10, 2984.. doi: 10.3390/electronics10232984
  
• [2931] R. Alamoudi, O. Taylan, M.A. Aktacir, E. Herrera-Viedma. Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches. Mathematics 2021, 9, 2929.. doi: 10.3390/math9222929
  
• [2936] J. Cascón-Katchadourian, J. Guallar. Software for managing audiovisual archives of cultural heritage Dédalo. Profesional de la Información 30:1 (2021). doi: 10.3145/epi.2021.ene.11
  
• [2937] J. Cascón-Katchadourian, J. Alberich-Pascual. The Georeferencing of Old Cartography in Geographic Information Systems (GIS): Review, Analysis and Comparative Study of Georeferencing Software. Revista General de Información y Documentación 31:1 (2021) 437-460. doi: 10.5209/rgid.76965
  
• [2947] C. Zuheros, E. Martínez-Cámara, E. Herrera-Viedma, F. Herrera. Sentiment Analysis based Multi-Person Multi-criteria Decision Making methodology using natural language processing and deep learning for smarter decision aid. Case study of restaurant choice using TripAdvisor reviews. Information Fusion 68 (2021) 22-36. doi: 10.1016/j.inffus.2020.10.019
  
• [2948] X. Chao, G. Kou, Y. Peng, E. Herrera-Viedma, F. Herrera. An efficient consensus reaching framework for large-scale social network group decision making and its application in urban resettlement. Information Fusion 575 (2021) 499-527. doi: 10.1016/j.ins.2021.06.047
  
• [2949] Y. Xu, Z. Gong, J.Y.-L. Forrest, E. Herrera-Viedma. Trust propagation and trust network evaluation in social networks based on uncertainty theory. Knowledge-Based Systems 234 (2021) 107610. doi: 10.1016/j.knosys.2021.107610
  
• [2950] A.K. Gupta, A. Seal, P. Khanna, E. Herrera-Viedma, O. Krejcar. ALMNet: Adjacent Layer Driven Multiscale Features for Salient Object Detection. IEEE Transactions on Instrumentation and Measurement 70 (2021) 2513214. doi: 10.1109/TIM.2021.3108503
  
• [3025] M. S. Kamal, A. Northcote, L. Chowdhury, N. Dey, R. Gonzalez-Crespo, E. Herrera-Viedma. Alzheimer’s Patient Analysis Using Image and Gene Expression Data and Explainable-AI to Present Associated Genes. IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-7, 2021, Art no. 2513107. doi: 10.1109/TIM.2021.3107056
  
• [3067] N. Rodríguez, D. López, A. Fernández, S. García, F. Herrera. SOUL: Scala Oversampling and Undersampling Library for imbalance classification. SoftwareX 15 (2021) 100767. doi: 10.1016/j.softx.2021.100767
  
• [3077] G. González-Almagro, J. Luengo, J.R. Cano, S. García. Enhancing instance-level constrained clustering through differential evolution. Applied Soft Computing 108, 107435. doi: 10.1016/j.asoc.2021.107435
  
• [3078] J. Carrasco, D. López, I. Aguilera-Martos, D. García-Gil, I. Markova, M. García-Bárzana, M. Arias-Rodil, J. Luengo, F. Herrera. Anomaly detection in predictive maintenance: A new evaluation framework for temporal unsupervised anomaly detection algorithms. Neurocomputing 462: 440-452 (2021). doi: 10.1016/j.neucom.2021.07.095
  
• [3079] M. González, J. Luengo, J. R. Cano, S. García. Synthetic Sample Generation for Label Distribution Learnin. Information Sciences 544: 197-213 (2021). doi: 10.1016/j.ins.2020.07.071
  
• [3080] J. Luengo, D. Sánchez Tarragó, R.C. Prati, F. Herrera. Multiple instance classification: Bag noise filtering for negative instance noise cleaning. Information Scences. 579: 388-400 (2021). doi: 10.1016/j.ins.2021.07.076
  
• [3081] G. González-Almagro, A. Rosales-Pérez, J. Luengo, J.R. Cano, S. García. ME-MEOA/DCC: Multiobjective constrained clustering through decomposition-based memetic elitism. Swarm Evolutionary Compututation 66: 100939 (2021).
  

2020 (75)

• [2603] S. Cobos-Guzman, E. Verdú, R. González-Crespo, E. Herrera-Viedma. Fuzzy logic expert system for selecting robotic hands using kinematic parameters. Journal of Ambient Intelligence and Humanized Computing 11 (2020) 1553–1564. doi: 10.1007/s12652-019-01229-x
  
• [2682] P. Lázaro-Rodríguez, J. López-Gijón, S. Alonso, E. Herrera-Viedma. Actualidad en estudios LibQUAL+®: paradigmas de la biblioteca informativa y social-creadora y cuestión de género como reflejos de la realidad social. Revista Española de Documentación Científica, v. 43 n. 2, e264.. doi: 10.3989/redc.2020.2.1649
  
• [2683] J.A. Morente-Molinera, X. Wu, A. Morfeq, R. Al-Hmouz, E. Herrera-Viedma. A novel multi-criteria group decision-making method for heterogeneous and dynamic contexts using multi-granular fuzzy linguistic modelling and consensus measures. Information Fusion, 53, 2020, 240-250.. doi: 10.1016/j.inffus.2019.06.028
  
• [2709] B. Farhadinia, E. Herrera-Viedma. A vertical ranking technique for linguistic hesitant fuzzy sets. Soft Computing 24 (2020) 8997–9009. doi: 0.1007/s00500-019-04426-0
  
• [2714] P. Lázaro-Rodríguez, J. López-Gijón, E. Herrera-Viedma.. Bibliotecas y eficiencia: adaptación del indicador de la Potencia del Sistema de la metodología Secaba-Rank para nuevas necesidades al servicio de una sociedad cambiante. BiD: textos universitaris de biblioteconomia i documentació, n. 44 (junio).
  
• [2718] Z. Gong, W. Guo, E. Herrera-Viedma, Z. Gong, G. Wei. Consistency and consensus modeling of linear uncertain preference relations. EJOR, Volume 283, Issue 1, 16 May 2020, Pages 290-307..
  
• [2719] A. Taghavi, E. Eslami, E. Herrera-Viedma, R. Ureña. Trust based group decision making in environments with extreme uncertainty. KNOSYS, Volume 191, 5 March 2020, 105168..
  
• [2720] Q. Zha, Y Dong, H Zhang, F Chiclana , and E Herrera-Viedma. A Personalized Feedback Mechanism Based on Bounded Confidence Learning to Support Consensus Reaching in Group Decision Making. IEEE Trans. Syst. Man and Cyb: Systems, 51:6, Pages 3900-3910.. doi: 10.1109/TSMC.2019.2945922
  
• [2721] F.J. Cabrerizo, R. Al-Hmouz, A. Morfeq, M.A. Martínez, W. Pedrycz, E. Herrera-Viedma. Estimating incomplete information in group decision making: A framework of granular computing. Applied Soft Computing 86 (2020) 105930. doi: 10.1016/j.asoc.2019.105930
  
• [2727] J. Tang, F. Meng, F.J. Cabrerizo, E. Herrera-Viedma. Group decision making with interval-valued intuitionistic multiplicative linguistic preference relations. Group Decision and Negotiation 29 (2020) 169-206. doi: 10.1007/s10726-019-09646-1
  
• [2728] A. Yazidi, H. Hammer, K. Samouylov, E. Herrera-Viedma. Game-Theoretic Learning for Sensor Reliability Evaluation without Knowledge of the Ground Truth. IEEE Transactions on Cybernetics (Volume: 51, Issue: 12, December 2021) Pages: 5706 – 5716. doi: 10.1109/TCYB.2019.2958616
  
• [2736] A. B. Arrieta, N. Díaz-Rodríguez, J. Del Ser, A. Bennetot, S. Tabik, A. Barbado, S. García, S. Gil-Robles, D. Molina, R. Benjamins, R. Chatila, F. Herrera. Explainable ArtificialIntelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58 (2020) 82-115. doi: 10.1016/j.inffus.2019.12.012
  
• [2740] J. Bernabé-Moreno, A. Tejeda-Lorente, J. Herce-Zelaya, C. Porcel, E. Herrera-Viedma. A context-aware embeddings supported method to extract a fuzzy sentiment polarity dictionary. KNOSYS, Vol. 190, 29 February 2020, 105236.. doi: 10.1016/j.knosys.2019.105236
  
• [2742] J.A. Moral-Muñoz, E. Herrera-Viedma, A. Santisteban-Espejo, M.J. Cobo. Software tools for conducting bibliometric analysis in science: An up-to-date review. Profesional de la información, 29:1, e290103. (2020). doi: 10.3145/epi.2020.ene.03
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• [2743] A. Kirimtat, O. Krejcar, A. Selamat, E. Herrera-Viedma. FLIR vs SEEK thermal cameras in biomedicine: comparative diagnosis through infrared thermography. BMC Bioinformatics 21 (2020) 88. doi: 10.1186/s12859-020-3355-7
  
• [2745] R-X. Ding, I. Palomares, X. Wang, G-R. Yang, B. Liu, Y. Dong, E. Herrera-Viedma, F. Herrera. Large-Scale decision-making: Characterization, taxonomy, challenges and future directions from an Artificial Intelligence and applications perspective. Information Fusion 59 (2020) 84-102. doi: 10.1016/j.inffus.2020.01.006
  
• [2749] W. Arroyo-Machado, D. Torres-Salinas, E. Herrera-Viedma, E. Romero-Frías. Science through Wikipedia: A novel representation of open knowledge through co-citation networks. PLoS ONE 15:2 (2020) e022871. doi: 10.1371/journal.pone.0228713
  
• [2750] F. Meng, J. Tang, F.J. Cabrerizo, E. Herrera-Viedma. A rational and consensual method for group decision making with interval-valued intuitionistic multiplicative preference relations. Engineering Applications of Artificial Intelligence 90 (2020) 103514. doi: 10.1016/j.engappai.2020.103514
  
• [2751] H. Zhang, J. Xiao, Y. Dong, F. Chiclana, E. Herrera-Viedma. Personalized individual semantics-based approach for linguistic failure modes and effects analysis with incomplete preference information. Institute of Industrial and Systems Engineers (IISE) Transactions 52:11 (2020) 1275-1296. doi: 10.1080/24725854.2020.1731774
  
• [2752] J.A. Morente-Molinera, F.J. Cabrerizo, J. Mezei, C. Carlsson, E. Herrera-Viedma. A dynamic group decision making process for high number of alternatives using hesitant fuzzy ontologies and sentiment analysis. Knowledge-Based Systems, Volume 195, 11 May 2020, 105657.. doi: 10.1016/j.knosys.2020.105657
  
• [2753] D. Cavaliere, J.A. Morente-Molinera, V. Loia, S. Senatore, E. Herrera-Viedma. Collective scenario understanding in a multi-vehicle system by consensus decision making. IEEE Transactions on Fuzzy Systems 28:9 (2020) 1984-1995. doi: 10.1109/TFUZZ.2019.2928787
  
• [2756] R. Ureña, F. Chiclana, A. Gonzalez-Alvarez, E. Herrera-Viedma, J. A. Moral-Munoz. m-SFT: A Novel Mobile Health System to Assess the Elderly Physical Condition. Sensors 20:5 (2020) 1462. doi: 10.3390/s20051462
  
• [2763] D. Cavaliere, J.A. Morente-Molinera, S. Senatore, E. Herrera-Viedma. An agent-based modeling for collective scene criticality assessment in multi-UV systems. Journal of Ambient Intelligence and Humanized Computing 11 (2020) 5153–5165. doi: 10.1007/s12652-020-01830-5
  
• [2765] R. Ureña, F. Chiclana, E. Herrera-Viedma. DeciTrustNET: A graph based trust and reputation framework for social networks. Information Fusion, Volume 61, September 2020, Pages 101-112..
  
• [2766] J.A. Morente-Molinera, F.J. Cabrerizo, S. Alonso, M.A. Martínez, E. Herrera-Viedma. Using multi-granular fuzzy linguistic modelling methods to represent social networks related information in an organized way. International Journal of Computers Communications & Control 15:2 (2020) 3851. doi: 10.15837/ijccc.2020.2.3851
  
• [2767] R. Gupta, M. Khari, V. Gupta, E. Verdú, Xing Wu, E. Herrera-Viedma, R. Gonzalez Crespo. Fast Single Image Haze Removal Method for Inhomogeneous Environment Using Variable Scattering Coefficient. Computer Modeling in Engineering and Sciences 123:2 (2020) 1175-1192. doi: 10.32604/cmes.2020.010092
  
• [2769] O. Taylan, R. Alamoudi, M. Kabli, A. AlJifri, F. Ramzi, E. Herrera-Viedma. Assessment of Energy Systems Using Extended Fuzzy AHP, Fuzzy VIKOR, and TOPSIS Approaches to Manage Non-Cooperative Opinions. Sustainability 12 (2020) 2745. doi: 10.3390/su12072745
  
• [2856] J. Guallar, J.R. López-Robles, E. Abadal, N.K. Gamboa-Rosales, M.J. Cobo. Spanish Information Science journals in Web of Science: bibliometric analysis and thematic evolution from 2015 to 2019. Profesional de la información, v. 29, n. 6, e290606. 2020. doi: 10.3145/epi.2020.nov.06
  
• [2771] W. Xie, Z. Xu, Z. Ren, E. Herrera-Viedma. A new multi-criteria decision model based on incomplete dual probabilistic linguistic preference relations. ASOC, Volume 91, June 2020, 106237.
  
• [2772] A.I. Maghsoodi, D. Riahi, E. Herrera-Viedma, E.K. Zavadskas. An integrated parallel big data decision support tool using the W-CLUS-MCDA: A multi-scenario personnel assessment. Knowledge-Based Systems 195 (2020) 105749. doi: 10.1016/j.knosys.2020.105749
  
• [2776] J. Cascón-Katchadourian, J.A. Moral-Muñoz, H. Liao, M.J. Cobo. Análisis bibliométrico de la Revista Española de Documentación Científica desde su inclusión en la Web of Science (2008-2018). Revista Española de Documentación científica. doi: 10.3989/redc.2020.3.1690
  
• [2777] H. D. Nguyen, N. V. Do, V. T. Pham, A. Selamat, E. Herrera-Viedma. A method for knowledge representation to design Intelligent Problems Solver in mathematics based on Rela-Ops model. IEEE Access,(Volume: 8), Pages: 76991 – 77012. doi: 10.1109/ACCESS.2020.2988929
  
• [2778] G. Kou, X. Chao, Y. Peng, F. E. Alsaadi, E. Herrera-Viedma. Machine learning methods for systemic risk analysis in financial sectors. Technological and Economic Development of Economy, 25(5), 716-742. doi: 10.3846/tede.2019.8740
  
• [2780] S. J. Fong, G. Lib, Ni. Dey, R. González Crespo, E. Herrera-Viedma. Composite Monte Carlo decision making under high uncertainty of novel coronavirus epidemic using hybridized deep learning and fuzzy rule induction. Applied Soft Computing, Volume 93, August 2020, 106282. doi: 10.1016/j.asoc.2020.106282
  
• [2781] M. Santana, M.J. Cobo. What is the future of work? A science mapping analysis. European Management Journal 38:6, 846-862, 2020. doi: 10.1016/j.emj.2020.04.010
  
• [2790] J. Maillo, S. García, J. Luengo, F. Herrera, I. Triguero. Fast and Scalable Approaches to Accelerate the Fuzzy k Nearest Neighbors Classifier for Big Data. IEEE Transactions on Fuzzy Systems 28(5): 874-886 (2020). doi: 10.1109/TFUZZ.2019.2936356
  
• [2795] W. Ding, CT. Lin, AWC. Liew, I. Triguero, W. Luo. Current trends of granular data mining for biomedical data analysis. Information Sciences, 2020, 510 pp. 341 - 343.
  
• [2797] M. Jiménez, MT. Torres, R. John, I. Triguero. Galaxy Image Classification Based on Citizen Science Data: A Comparative Study. IEEE Access 8, 47232-47246.
  
• [2798] J.C. Bailón-Elvira, M.J. Cobo, A.G. López-Herrera. Boletín Oficial del Estado: análisis de metadatos, detección de errores y recomendaciones de mejora. Profesional de la información, v. 29, n. 2, e290226. doi: 10.3145/epi.2020.mar.26
  
• [2799] A. Anguita-Ruiz, A. Segura-Delgado, R. Alcalá, C.M. Aguilera, J. Alcalá-Fdez. eXplainable Artificial Intelligence (XAI) for the identification of biologically relevant gene expression patterns in longitudinal human studies, insights from obesity research. PLoS Computational Biology 16:4 (2020) 1-34. doi: 10.1371/journal.pcbi.1007792
  
• [2800] A. Segura-Delgado, M.J. Gacto, R. Alcalá, J. Alcalá-Fdez. Temporal association rule mining: An overview considering the time variable as an integral or implied component. Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery 10:4 (2020) e1367. doi: 10.1002/widm.1367
  
• [2801] N. Wua, Y. Xua, X. Liua, H. Wang, E. Herrera-Viedma. Water-Energy-Food nexus evaluation with a social network group decision making approach based on hesitant fuzzy preference relations. ASOC, Volume 93, August 2020, 106363..
  
• [2802] P. Lázaro-Rodríguez, E. Herrera-Viedma. Noticias sobre Covid-19 y 2019-nCoV en medios de comunicación de España: el papel de los medios digitales en tiempos de confinamiento. El profesional de la información, v. 29, n. 3, e290302. 2020. doi: 10.3145/epi.2020.may.02
  
• [2803] H. Seiti, A. Hafezalkotob, E. Herrera-Viedma. A Novel Linguistic Approach for Multi-Granular Information Fusion and Decision-Making Using Risk-Based Linguistic D Numbers. Information Sciences 530 (2020) 43-65.
  
• [2804] M. Gutiérrez-Salcedo, J.R. López-Robles, M.A. Martínez-Sánchez, E. Herrera-Viedma, M.J. Cobo. Identification and visualization of the conceptual structure and main research themes of Studies in Informatics and Control journal from 2008 to 2019. Studies in Informatics and Control, 29:2, pp. 159-168, 2020. doi: 10.24846/v29i2y202002
  
• [2805] J. Herce-Zelaya, C. Porcel, J. Bernabé-Moreno, A. Tejeda-Lorente, E. Herrera-Viedma. New technique to alleviate the cold start problem in recommender systems using information from social media and random decision forests. Information Sciences, volumen 536, 156-170, 2020. doi: 10.1016/j.ins.2020.05.071
  
• [2806] F.J. Cabrerizo, M. Heikkilä, J. Mezei, J.A. Morente-Molinera, E. Herrera-Viedma, C. Carlsson. Granular fuzzy pay-off method for real option valuation. Expert Systems with Applications 159 (2020) 113597. doi: 10.1016/j.eswa.2020.113597
  
• [2808] C. Panigrahy, A. Seal, N. Kumar Mahato, O. Krejcar, E. Herrera-Viedma. Multi-focus Image Fusion using Fractal Dimension. Applied Optics 59:19 (2020) 5642-5655. doi: 10.1364/AO.391234
  
• [2809] E. Herrera-Viedma, J.R. López-Robles, J. Guallar, M.J. Cobo. Global trends in coronavirus research at the time of Covid-19: A general bibliometric approach and content analysis using SciMAT. Profesional de la información, 29:3 (2020), e290322. doi: 10.3145/epi.2020.may.22
  
• [2810] X. Tian, M. Niu, W. Zhang, L. Li, E. Herrera-Viedma. A novel TODIM based on prospect theory to select green supplier with q-rung orthopair fuzzy set. Technological and Economic Development of Economy, 2021 Volume 27 Issue 2: 284–310. doi: 10.3846/tede.2020.12736
  
• [2811] P. Lázaro-Rodríguez. Bibliotecas y efecto Pigmalión: la importancia de la interpretación de resultados y otras cuestiones metodológicas a partir de una crítica al Barómetro de hábitos de lectura y compra de libros en España de 2019. Anuario ThinkEPI, v. 14, e14b01. doi: 10.3145/thinkepi.2020.e14b01
  
• [2812] P. Lázaro-Rodríguez. Covid-19, medios digitales y Facebook: interacciones, tratamiento y análisis de contenido basado en palabras clave de noticias de okdiario.com y eldiario.es. Profesional de la información. v. 29, n. 4, e290409.
  
• [2819] J. Cascón-Katchadourian, J. Alberich, A. Quesada-Román. Revisión y sistematización del proceso de digitalización y publicación de cartografía antigua en medios digitales. Investigación Bibliotecológica, 34:83 (2020) 13-35. doi: 10.22201/iibi.24488321xe.2020.83.58137
  
• [2828] E. Crisol, L. Herrera, R. Montes. Educación virtual para todos: una revisión sistemática. Education in the Knowledge Society (EKS) 21:0, 2020. doi: 10.14201/eks.20327
  
• [2829] C. Porcel, J. Herce-Zelaya, J. Bernabé-Moreno, A. Tejeda-Lorente, E. Herrera-Viedma. Trust Based Fuzzy Linguistic Recommender Systems as Reinforcement for Personalized Education in the Field of Oral Surgery and Implantology. International Journal Of Computers Communications & Control. [S.l.], v. 15, n. 3, apr. 2020. ISSN 1841-9844.. doi: 10.15837/ijccc.2020.3.3858
  
• [2830] P. Sánchez-Núñez, M.J. Cobo, C. de las Heras-Pedrosa, J.I. Peláez, E. Herrera-Viedma. Opinion Mining, Sentiment Analysis and Emotion Understanding in Advertising: A Bibliometric Analysis. IEEE Access, 8, pp. 134563-134576, (2020). doi: 10.1109/ACCESS.2020.3009482
  
• [2833] L. Bertolin-Furstenau, Mi. Kremer-Sott, L. M-Kipper, Ê.L. Machado, J.R López-Robles, M.S. Dohan., M.J. Cobo, A. Zahid, Q.H. Abbasi, M. Ali Imran. Link between sustainability and industry 4.0: trends, challenges and new perspectives. IEEE Access, 8, pp. 140079-140096, (2020). doi: 10.1109/ACCESS.2020.3012812
  
• [2838] R. González-Crespo, E. Herrera-Viedma, N. Dey, S. J. Fong, G. Li. Finding an Accurate Early Forecasting Model from Small Dataset: A Case of 2019-nCoV Novel Coronavirus Outbreak. IJIMAI, 6:1, (2020) pp. 132-140..
  
• [2839] M.K. Sott, L.B. Furstenau, L.M. Kipper, F.D. Giraldo, J.R. López-Robles, M.J. Cobo, A. Zahid, Q.H. Abbasi, M.A. Imran. Precision Techniques and Agriculture 4.0 Technologies to Promote Sustainability in the Coffee Sector: State of the Art, Challenges and Future Trends. IEEE Access, 8, pp. 149854-149867, (2020). doi: 10.1109/ACCESS.2020.3016325
  
• [2841] J.T. Ellis, B. Ellis, A. Velez-Estevez, M.P. Reichel, M.J. Cobo. 30 years of parasitology research analysed by text mining. Parasitology 147:14, pp. 1643 - 1657. 2020. doi: 10.1017/S0031182020001596
  
• [2842] J. Cascón-Katchadourian. Tecnologías para luchar contra la pandemia Covid-19: geolocalización, rastreo, big data, SIG, inteligencia artificial y privacidad. Profesional de la información 29:4 (2020) e290429. doi: 10.3145/epi.2020.jul.29
  
• [2843] P. Lázaro-Rodríguez. COBib-Públicas: observatorio de las bibliotecas públicas en España durante la pandemia por Covid-19 basado en noticias digitales. Anuario ThinkEPI, v. 14, e14b01.. doi: 10.3145/thinkepi.2020.e14b04
  
• [2845] J. Cascón-Katchadourian. Identification and analysis of the H-Classics of andalusian of public universities in the economics category of the journal citation (JCR). Revista de Estudios Empresariales. Segunda Epoca 1 (2020) 75-90. doi: 10.17561//ree.v2020n1.6
  
• [2847] D. Molina, J. Poyatos, J.D. Del Ser, S. García, A. Hussain, F. Herrera. Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations. Cognitive Computation 12:5 (2020) 897-939. doi: 10.1007/s12559-020-09730-8
  
• [2849] J.A. Morente-Molinera, F.J. Cabrerizo, S. Alonso, I.J. Pérez, E. Herrera-Viedma. Assisting users in decisions using fuzzy ontologies: Application in the wine market. Mathematics 8:10 (2020) 1724. doi: 10.3390/math8101724
  
• [2850] S. Ramadass, K. Raghunathan, K. S. Ravichandran, H. Liao, S. Kar, E. Herrera-Viedma. Evaluation of cloud vendors from probabilistic linguistic information with unknown/partial weight values. Applied Soft Computing 97 (2020) 106801. doi: 10.1016/j.asoc.2020.106801
  
• [2852] O. Gómez, O. Ibáñez, A. Valsecchi, E. Bermejo, D. Molina, O. Cordón. Performance analysis of real-coded evolutionary algorithms under a computationally expensive optimization scenario: 3D–2D Comparative Radiography. Applied Soft Computing 97:A (2020) 106793. doi: 10.1016/j.asoc.2020.106793
  
• [2857] R. Heradio, D. Fernandez-Amoros, C. Cerrada, M.J. Cobo. Group Decision-Making Based on Artificial Intelligence: A Bibliometric Analysis. Mathematics 2020, 8(9), 1566. doi: 10.3390/math8091566
  
• [2866] M.K. Sott, M.S. Bender, L.B. Furstenau, L.M. Machado, M.J. Cobo, N.L. Bragazzi. 100 Years of Scientific Evolution of Work and Organizational Psychology: A Bibliometric Network Analysis From 1919 to 2019. Frontiers in Psychology 11, pp. 3411. 2020. doi: 10.3389/fpsyg.2020.598676
  
• [2951] A.I. Maghsoodi, S. Soudian, L. Martínez, E. Herrera-Viedma, E.K. Zavadskas. A phase change material selection using the interval-valued target-based BWM-CoCoMULTIMOORA approach: A case-study on interior building applications. Applied Soft Computing 95 (2020) 106508. doi: 10.1016/j.asoc.2020.106508
  
• [2960] A. Anguita-Ruiz, E.M. González-Gil, A.I. Rupérez, F.J. Llorente-Cantarero, B. Pastor-Villaescusa, J. Alcalá-Fdez, L.A. Moreno, Á. Gil, M. Gil-Campos, G. Bueno, R. Leis, C.M. Aguilera. Evaluation of the Predictive Ability, Environmental Regulation and Pharmacogenetics Utility of a BMI-Predisposing Genetic Risk Score during Childhood and Puberty. Journal of Clinical Medicine 9:6 (2020) 1705. doi: 10.3390/jcm9061705
  
• [3028] M.F. Khan, D. Goyal, M.M. Nofal, E. Khan, R. Al-Hmouz, E. Herrera-Viedma. Fuzzy-based Histogram Partitioning for Bi-Histogram Equalisation of Low Contrast Images. IEEE Access (Volume: 8) Pages: 11595 – 11614. doi: 10.1109/ACCESS.2020.2965174
  
• [3082] G. González-Almagro, J. Luengo, J. R. Cano, S. García. DILS: Constrained clustering through dual iterative local search. Computers & Operations Research 121: 104979 (2020). doi: 10.1016/j.cor.2020.104979
  
• [3083] J. A. Cortés-Ibáñez, S. González, J. J. Valle-Alonso, J. Luengo, S. García, F. Herrera. Preprocessing methodology for time series: An industrial world application case study. Inf. Sci. 514: 385-401 (2020). doi: j.ins.2019.11.027
  
• [3084] S. Tabik, A. Gómez-Ríos, J. L. Martín-Rodríguez, I. Sevillano-García, M. Rey-Area, D. Charte, E. Guirado, J.-L. Suárez, J. Luengo, M. A. Valero-González, P. García-Villanova, E. Olmedo-Sánchez, F. Herrera. COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images. IEEE Journal of Biomedical and Health Informatics 24(12): 3595-3605 (2020). doi: 10.1109/JBHI.2020.3037127
  

2019 (77)

• [2335] S. Elhag, A. Fernandez, A. Altalhi, S. Alshomrani, F. Herrera. A Multi-Objective Evolutionary Fuzzy System to Obtain a Broad and Accurate Set of Solutions in Intrusion Detection Systems. Soft Computing 23:4 (2019) 1321-1336. doi: 10.1007/s00500-017-2856-4
  
• [2391] E.A. Callejas, J.A. Cerrada, C. Cerrada, F.J. Cabrerizo. Group decision making based on a framework of granular computing for multi-criteria and linguistic contexts. IEEE Access 7 (2019) 54670-54681. doi: 10.1109/ACCESS.2019.2913338
  
• [2439] B. Farhadinia, E. Herrera-Viedma. Sorting of decision making methods based on their outcomes using dominance-vector hesitant fuzzy based distance. Soft Computing, 2019, Vol. 23, Issue 4, pp 1109–1121..
  
• [2447] J.M. Merigó, M.J. Cobo, S. Laengle, D. Rivas, E. Herrera-Viedma. Twenty years of Soft Computing: A bibliometric overview. Soft Computing, 23:5 pp 1477–1497 (2019). doi: 10.1007/s00500-018-3168-z
  
• [2669] Y. Dong, W. Liu, F. Chiclana, G. Kou, E. Herrera-Viedma. Are incomplete and self-confident preference relations better in multicriteria decision making? A simulation-based investigation.. Information Sciences, 492, 2019, 40-57..
  
• [2477] M. R. Ureña, F. Chiclana, G. Melancon, E. Herrera-Viedma. A social network based approach for consensus achievement in multiperson decision making. Information Fusion, 47 (2019) 72-87..
  
• [2485] J. Cózar, A. Fernandez, F. Herrera, J.A. Gámez. A Meta-Hierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity. IEEE Transactions on Fuzzy Systems 27:4 (2019) 701-715. doi: 10.1109/TFUZZ.2018.2866967
  
• [2488] Z. Zhaoa, X. Zhang, C. Li, F. Chiclana, E. Herrera-Viedma. An Incremental Method to Detect Communities in Dynamic Evolving Social Networks. Knowledge-Based Systems, 163 (2019) 404–415.
  
• [2490] A. Fernandez, M.J. de Jesus, O. Cordon, F. Marcelloni, F. Herrera. Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to?. IEEE Computational Intelligence Magazine 14:1 (2019) 69-81. doi: 10.1109/MCI.2018.2881645
  
• [2499] B. Farhadinia, F.J. Cabrerizo, E. Herrera-Viedma. Horizontal representation of a hesitant fuzzy set and its application to multiple attribute decision making. Iranian Journal of Fuzzy Systems 16:5 (2019) 1-13. doi: 10.22111/ijfs.2019.4900
  
• [2503] Y. Liu, Y. Dong, H.Liang, F. Chiclana, E. Herrera-Viedma. Multiple attribute strategic weight manipulation with minimum cost in a group decision making context with interval attribute weights information. IEEE Trans. Syst. Man and Cyb: Systems, (49):10 (2019) ,pp. 1981-1992..
  
• [2506] RC. Prati, J. Luengo, F. Herrera. Emerging topics and challenges of learning from noisy data in nonstandard classification: a survey beyond binary class noise. Knowledge and Information Systems 60(1): 63-97 (2019). doi: 10.1007/s10115-018-1244-4
  
• [2512] J.A. Morente-Molinera, G. Kou, C. Pang, F.J. Cabrerizo, E. Herrera-Viedma. An automatic procedure to create fuzzy ontologies from users' opinions using sentiment analysis procedures and multi-granular fuzzy linguistic modelling methods. Information Sciences 476 (2019) 222-238. doi: 10.1016/j.ins.2018.10.022
  
• [2513] R. Ureña, G. Kou, Y. Dong, F. Chiclana, E. Herrera-Viedma. A review on trust propagation and opinion dynamics in social networks and group decision making frameworks. Information Sciences, Volume 478, (2019) 461-475.
  
• [2516] N. Capuano, F. Chiclana, E. Herrera-Viedma, H. Fujita, V. Loia. Fuzzy Group Decision Making for Influence-Aware Recommendations. Computers in Human Behavior, Volume 101, December 2019, Pages 371-379.. doi: 10.1016/j.chb.2018.11.001
  
• [2523] A. Gómez-Ríos, S. Tabik, J. Luengo, ASM. Shihavuddin, B. Krawczyk, F. Herrera. Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation. Expert Systems with Applications 118 (2019) 315-328. doi: 10.1016/j.eswa.2018.10.010
  
• [2526] X. Mao, X. Zhao, J. Lin, E. Herrera-Viedma. Utilizing multi-source data in popularity prediction for shop-type recommendation. Knowledge-Based Systems, Volume 165, 1 February 2019, Pages 253-267. doi: 10.1016/j.knosys.2018.11.033
  
• [2534] J.A. Morente-Molinera, G. Kou, K. Samuylov, R. Ureña, E. Herrera-Viedma. Carrying out consensual Group Decision Making processes under social networks using sentiment analysis over comparative expressions. Knowledge-Based Systems, 165, 335-345. doi: 10.1016/j.knosys.2018.12.006
  
• [2543] I. Triguero, D. García-Gil, J. Maillo, J. Luengo, S. García, F. Herrera. Transforming big data into smart data: An insight on the use of the k nearest neighbors algorithm to obtain quality data. Wiley Interdisciplinary Reviews. Data Mining and Knowledge Discovery. e1289. doi: 10.1002/widm.1289
  
• [2544] C-C Li, Y. Dong, Y. Xu, F. Chiclana, E. Herrera-Viedma, F. Herrera. An overview on managing additive consistency of reciprocal preference relations for consistency-driven decision making and Fusion: Taxonomy and future directions. Information Fusion, Vol. 52, 2019, Pages 143-156..
  
• [2545] X. Liu, Y. Xu, R. Montes, R. Ding, F. Herrera. Alternative Ranking-Based Clustering and Reliability Index-Based Consensus Reaching Process for Hesitant Fuzzy Large Scale Group Decision Making. IEEE Transactions on Fuzzy Systems 27:1, 159-171, January 2019. doi: 10.1109/TFUZZ.2018.2876655
  
• [2554] X. Liu, Y. Xu, R. Montes, Y. Dong, F. Herrera. Analysis of self-confidence indices-based additive consistency for fuzzy preference relations with self-confidence and its application in group decision making. Int J Intell Syst. 34:5 (2019) 920-946. doi: 10.1002/int.22081
  
• [2555] B. Zhang, Y. Dong,E. Herrera-Viedma. Group decision making with heterogeneous preference structures: An automatic mechanism to support consensus reaching. Group Decision & Negotiation, 28:3, 585-617, 2019..
  
• [2556] F.M.A. Alias, L. Abdullah, H. Liao, E. Herrera-Viedma. Consistent Fuzzy Preference Relation with Geometric Bonferroni Mean: A Fused Preference Method for Assessing the Quality of Life. Applied Intelligence 49 (2019) 2672–2683. doi: 10.1007/s10489-019-01415-6
  
• [2557] D. García-Gil, J. Luengo, S. García, F. Herrera. Enabling smart data: noise filtering in big data classification. Information Sciences 479, 135-152. doi: 10.1016/j.ins.2018.12.002
  
• [2561] R. Urena, G. Kou, J. Wu, F. Chiclana, E. Herrera-Viedma. Dealing with Incomplete Information in Linguistic Group Decision Making by Means of Interval Type 2 Fuzzy Sets. Int. J. of Intelligent Systems, 2019;34:1261-1280..
  
• [2562] J.R. López-Robles, J.R. Otegi-Olaso, I. Porto-Gómez, M.J. Cobo. 30 Years of Intelligence Models in Management and Business: A Bibliometric Review. International Journal of Information Management, 48, pp 22-38 (2019). doi: 10.1016/j.ijinfomgt.2019.01.013
  
• [2564] L. Ruiz-González, D. Lucena-Antón, A. Salazar, R. Martín-Valero, J.A. Moral-Muñoz. Physical Therapy in Down Syndrome: Systematic review and Meta-analysis. Journal of Intellectual Disability Research.
  
• [2568] A. Castillo, S. Tabik, F. Pérez, R. Olmos, F. Herrera. Brightness guided preprocessing for automatic cold steel weapon detection in surveillance videos with deep learning. Neurocomputing 330(2019) 151-161. doi: 10.1016/j.neucom.2018.10.076
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• [2571] S. González, S. García, S-T. Li, F. Herrera. Chain based sampling for monotonic imbalanced classification. Information Sciences 474 (2019) 187-204. doi: 10.1016/j.ins.2018.09.062
  
• [2575] M. López, A. Valdivia, E. Martínez-Cámara, M.V. Luzón, F. Herrera. E2SAM: Evolutionary Ensemble of Sentiment Analysis Methods for Domain Adaptation. Information Sciences, 480 (2019) 273-286. doi: 10.1016/j.ins.2018.12.038
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• [2620] V. Perez-Cabezas, C. Ruiz-Molinero, B. Nuñez-Moraleda, J.J. Jimenez-Rejano, R. Chillon-Martinez, J.A. Moral-Muñoz. Guillain-Barre Syndrome and Zika infection: Identifying leading producers, countries relative specialization, and collaboration. FEMS Microbiology Letters.
  
• [2628] M. Jiménez, I. Triguero, R. John. Handling uncertainty in citizen science data: Towards an improved amateur-based large-scale classification. Information Sciences 479, 301-320. doi: 10.1016/j.ins.2018.12.011
  
• [2642] B. Farhadinia, E. Herrera-Viedma. Multiple criteria group decision making method based on extended hesitant fuzzy sets with unknown weight information. Applied Soft Computing, 78, 2019, 310-323..
  
• [2639] R. Tickle, I. Triguero, GP. Figueredo, M. Mesgarpour, R. John. PAS3-HSID: A Dynamic Bio-Inspired Approach for Real-time Hot Spot Identification in Data Streams. Cognitive Computation 11 (3), 434-458.
  
• [2640] J.M. Soto-Hidalgo, A. Vitiello, J.M. Alonso, G. Acampora, J. Alcalá-Fdez. Design of Fuzzy Controllers for Embedded Systems With JFML. International Journal of Computational Intelligence Systems 12:1 (2019) 204-214. doi: 10.2991/ijcis.2019.125905646
  
• [2641] J. Tang, F. Meng, F.J. Cabrerizo, E. Herrera-Viedma. A procedure for group decision making with interval-valued intuitionistic linguistic fuzzy preference relations. Fuzzy Optimization and Decision Making 18:4 (2019) 493-527. doi: 10.1007/s10700-019-09304-w
  
• [2663] P. Lázaro-Rodríguez, J. López-Gijón, E. Herrera-Viedma. Secaba-Rank a examen: validación de su metodología sobre eficiencia en bibliotecas versus la técnica Data Envelopment Analysis (DEA) y el método Finlandia. El profesional de la Información, v. 28, n. 3, e280316. doi: 10.3145/epi.2019.may.16
  
• [2666] J.A. Morente-Molinera, S.Ríos-Aguilar, R. González-Crespo, E. Herrera-Viedma. Dealing with group decision making environments that have a high amount of alternatives using card-sorting techniques. Expert systems with applications 127 (2019) 187-198.
  
• [2667] JR. Cano, J. Luengo, S. García. Label Noise Filtering Techniques to Improve Monotonic Classification. Neurocomputing 353: 83-95 (2019). doi: 10.1016/j.neucom.2018.05.131
  
• [2668] Y. Dong, Y. Fan, H. Liang, F. Chiclana, E. Herrera-Viedma. Preference evolution with deceptive interactions and heterogeneous trust in bounded confidence model: A simulation analysis. Knowledge-Based Systems. 175, 2019, 87-95..
  
• [2670] H. Liao, L. Abdullah, N. Zulkifli, E. Herrera-Viedma, A. Al-Barakati. An interval-valued intuitionistic fuzzy DEMATEL method combined with Choquet integral for sustainable solid waste management. Engineering Applications of Artificial Intelligence, 82, 207-215, 2019..
  
• [2672] J.A. Moral-Muñoz, L. Carballo-Costa, E. Herrera-Viedma, M.J. Cobo. Production trends, collaboration, and main topics of the Integrative & Complementary Oncology research area: A bibliometric analysis. Integrative Cancer Therapies 18 (2019) 1-14. doi: 10.1177/1534735419846401
  
• [2674] H. Ordoñez, J. Torres-Jimenez, C.Cobos, A. Ordoñez, E. Herrera-Viedma, Gildardo Maldonado-Martinez. A business process clustering algorithm using incremental covering arrays to explore search space and balanced Bayesian information criterion to evaluate quality of solutions. PLoS ONE 14:6 (2019) e021768. doi: 10.1371/journal.pone.0217686
  
• [2675] N. Robinson-Garcia, D. Torres-Salinas, E. Herrera-Viedma, D. Docampo. Mining university rankings: Publication output and citation impact as their basis. Research Evaluation, 28:3, 2019, 232–240..
  
• [2676] W. Xie, Z. Xu, Z. Ren, E. Herrera-Viedma. Expanding grey relational analysis with the comparable degree for dual probabilistic multiplicative linguistic term sets and its application on the cloud enterprise. IEEE Access, Vol. 7 (2019) pp. 75041 - 75057.
  
• [2677] J.A. Moral-Muñoz, W. Zhang, M.J. Cobo, E. Herrera-Viedma, D.B. Kaber. Smartphone-based systems for physical rehabilitation applications: A systematic review. Assistive Technology, 33:4 (2019) 223-236. doi: 10.1080/10400435.2019.1611676
  
• [2680] H. Ordoñez, J. Torres-Jimenez, C. Cobos, A. Ordoñez, E. Herrera-Viedma, G. Maldonado-Martinez. A Business Process Clustering Algorithm Using Incremental Covering Arrays to Explore Search Space and Balanced Bayesian Information Criterion to Evaluate Quality of Solutions. PLoS ONE 14(6): e0217686. https://doi.org/10.1371/journal.pone.0217686..
  
• [2681] C. Moreno, R. A. Carrasco, E. Herrera-Viedma. Data and Artificial Intelligence Strategy: A Conceptual Enterprise Big Data Cloud Architecture to Enable MarketOriented Organisations. International Journal of Interactive Multimedia and Artificial Intelligence, 5:6 (2019) pp. 7-14. doi: 10.9781/ijimai.2019.06.003
  
• [2684] X. Mi, J. Li, H. Liao, E.K.Zavadskas, A. Al-Barakati, O. Taylan, E. Herrera-Viedma. Hospitality brand management by a score-based q-rung orthopair fuzzy VIKOR method integrated with the best worst method. Economic Research-Ekonomska Istraživanja 32:1 (2019) 3272-3301. doi: 10.1080/1331677X.2019.1658533
  
• [2685] O. Krejcar, P. Maresova, A. Selamat, F. Jose Melero, S. Barakovic, J. Barakovic-Husic, E. Herrera-Viedma, R. Frischer, K. Kuca. Smart Furniture as a Component of a Smart City - Definition Based on Key Technologies Specification. IEEE Access 7 (2019) 94822-94839. doi: 10.1109/ACCESS.2019.2927778
  
• [2686] Bio-inspired computation: Where we stand and what's next. J. Del Ser, E. Osaba, D. Molina, X.S. Yang, S. Salcedo-Sanz, D. Camacho, S. Das, P.N. Suganthan, C.A. Coello Coello, F. Herrera. Swarm and Evolutionary Computation, 48 (2019) 220-250.. doi: 10.1016/j.swevo.2019.04.008
  
• [2687] F. Blanco-Mesa, E. León-Castro, J. M. Merigó, E. Herrera-Viedma. Variances with Bonferroni means and ordered weighted averages. International Journal of Intelligent Systems 34:11 (2019) 3020-3045. doi: 10.1002/int.22184
  
• [2688] X. Liu, Y. Xu, R. Montes, F. Herrera. Social network group decision making: Managing self-confidence based consensus model with dynamic importance degree of experts and trust-based feedback mechanism. Information Sciences 505 (2019) 215-232. doi: j.ins.2019.07.050
  
• [2689] Y. Xu, Y. Xi, F.J. Cabrerizo, E. Herrera-Viedma. An alternative consensus model of additive preference relations for group decision making based on the ordinal consistency. International Journal of Fuzzy Systems 21:6 (2019) 1818-1830. doi: 10.1007/s40815-019-00696-w
  
• [2690] J. Del Ser, E. Osaba, D. Molina, Xin-She Yang, S. Salcedo-Sanz, D. Camacho, S. Das, P. N.Suganthan, C. A.Coello, F. Herrera. Bio-inspired computation: Where we stand and what's next. Swarm and Evolutionary Computation 48 (2019) 220-250. doi: 10.1016/j.swevo.2019.04.008
  
• [2691] M. Leon, N. Xiong, D. Molina, F. Herrera. A Novel Memetic Framework for Enhancing Differential Evolution Algorithms via Combination With Alopex Local Search. International Journal of Computational Intelligence Systems 12:2 (2019) 795-808. doi: 10.2991/ijcis.d.190711.001
  
• [2694] Y. Wei, X. Zhao, J. Zou, E. Herrera-Viedma. A location complementing preference based method for location recommendation with cellular data. Knowledge-Based Systems 183 (2019) 104889. doi: 10.1016/j.knosys.2019.104889
  
• [2695] M.J. Gacto, J.M. Soto-Hidalgo, J. Alcalá-Fdez, R. Alcalá. Experimental Study on 164 Algorithms Available in Software Tools for Solving Standard Non-Linear Regression Problems. IEEE Access 7 (2019) 108916-108939. doi: 10.1109/ACCESS.2019.2933261
  
• [2708] A. Fernandez, I. Triguero, M. Galar, F. Herrera. Guest Editorial: Computational Intelligence for Big Data Analytics. Cognitive Computation 11 (2019) 329–330. doi: 10.1007/s12559-019-09647-x
  
• [2730] Q. Zha, Y. Dong, H. Zhang, F Chiclana, E Herrera-Viedma. A Personalized Feedback Mechanism Based on Bounded Confidence Learning to Support Consensus Reaching in Group Decision Making. IEEE Trans. Syst. Man and Cyb: Systems, 51:6 (2019) 3900 - 3910. doi: 10.1109/TSMC.2019.2945922
  
• [2746] I. A. Rodriguez, R. Ureña, E. Herrera-Viedma. Fuzzy clustering approach for brain tumor tissue segmentation in magnetic resonance images. Soft Computing. 2019, 23:20, pp 10105–10117..
  
• [2747] F. M. Anira-Alias, L. Abdullah, H. Liao, E. Herrera-Viedma. Consistent Fuzzy Preference Relation with Geometric Bonferroni Mean: A Fused Preference Method for Assessing the Quality of Life. Applied Intelligence, 2019, 49:7, pp 2672–2683..
  
• [2754] L. Herrera, E. Crisol, R. Montes. A MOOC on universal design for learning designed under the UDL paradigm. Australasian Journal of Educational Technology 35:6 (2019) 30–47. doi: 10.14742/ajet.5532
  
• [2783] W. Ding, GG. Yen, G. Beliakov, I. Triguero, M. Pratama, X. Zhang, H Li. IEEE Access Special Section Editorial: Data Mining and Granular Computing in Big Data and Knowledge Processing. IEEE Access 7, 47682-47686.
  
• [2784] JS. Angarita-Zapata, AD. Masegosa, I. Triguero. A Taxonomy of Traffic Forecasting Regression Problems From a Supervised Learning Perspective. IEEE Access 7, 68185-68205.
  
• [2785] H. Song, I. Triguero, E. Özcan. A review on the self and dual interactions between machine learning and optimisation. Progress in Artificial Intelligence 8 (2), 143-165.
  
• [2787] M. Aboufoul, A. Chiarelli, I. Triguero, A. Garcia. Virtual porous materials to predict the air void topology and hydraulic conductivity of asphalt roads. Powder Technology 352, 294-304.
  
• [2791] T. Wei, J. Zhou, R. Ranjan, I. Triguero, H. Yu, CJ. Xue, S. Dustdar. Introduction to the Special Issue on Human-interaction-aware Data Analytics for Cyber-physical Systems. ACM Transactions on Cyber-Physical Systems 3 (4), 1-2.
  
• [2792] M. Canizo, I. Triguero, A. Conde, E. Onieva. Multi-head CNN–RNN for multi-time series anomaly detection: An industrial case study. Neurocomputing 363, 246-260.
  
• [2817] J. Cascón-Katchadourian, A.G. López-Herrera, A.A. Ruíz-Rodríguez, E. Herrera-Viedma. Proyecto Histocarto, aplicación de SIGs (georreferenciación y geolocalización) para mejorar la recuperación de la documentación histórica gráfica. El profesional de la información 28:4 (2019) e280416.. doi: 10.3145/epi.2019.jul.16
  
• [2818] J. Cascón-Katchadourian, A.A. Ruíz-Rodríguez, E. Herrera-Viedma. Definición, legislación y normativa para el tratamiento de los documentos históricos generados en la Administración Pública española y andaluza. Revista Española de Documentación Científica 42:4 (2019) e249.. doi: 10.3989/redc.2019.4.1653
  
• [2837] R. A. Carrasco, M. F. Blasco, J. García-Madariaga, E. Herrera-Viedma. A Fuzzy Linguistic RFM Model Applied to Campaign Management. International Journal of Interactive Multimedia and Artificial Intelligence 5:4 (2019) pp. 21-27.
  
• [2973] E. Meza, B. Sicardy, ..., S. Alonso, et al.. Lower atmosphere and pressure evolution on Pluto from ground-based stellar occultations, 1988–2016. Astronomy and Astrophysics 629 (2019) A42. doi: 10.1051/0004-6361/201834281
  
• [3088] D. García-Gil, F. Luque Sánchez, J. Luengo, S. García, F. Herrera. From Big to Smart Data: Iterative ensemble filter for noise filtering in Big Data classification. International Journal of Intelligent Systems 34(12): 3260-3274 (2019). doi: 10.1002/int.22193
  
• [3089] I. Cordón, J. Luengo, S. García, F. Herrera, F. Charte. Smartdata: Data preprocessing to achieve smart data in R. Neurocomputing 360: 1-13 (2019). doi: 10.1016/j.neucom.2019.06.006
  
• [3090] A. Gómez-Ríos, S. Tabik, J. Luengo, A.S.M. Shihavuddin, F. Herrera. Coral species identification with texture or structure images using a two-level classifier based on Convolutional Neural Networks.. Knowledge-Based Systems 184 (2019). doi: j.knosys.2019.104891
  

2018 (118)

• [2019] K. Trawinski, M. Chica, D.P. Pancho, S. Damas, O. Cordón. moGrams: a network-based methodology for visualizing the set of non-dominated solutions in multiobjective optimization. IEEE Transactions on Cybernetics 48:2 (2018) 474-485. doi: 10.1109/TCYB.2016.2642886
  
• [2030] K. Srikantha, L.K. Panwar, B.K. Panigrahi, E. Herrera-Viedma, A.K. Sangaiah, G.-G. Wang. Meta-heuristic framework: Quantum inspired binary grey wolf optimizer for unit commitment problem. Computer & Electrical Engineering Volume 70, August 2018, Pages 243-260.. doi: 10.1016/j.compeleceng.2017.07.023
  
• [2402] J. Albadán-Romero, P. Gaona-García, G. Rolong-Agudelo, C. Montenegro-Marin, R. Gonzalez-Crespo, E. Herrera-Viedma. Fuzzy Logic Models for Non-Programmed Decision-Making in Personnel Selection Processes Based on Gamification. Informatica 29:1 (2018) 1-20. doi: 10.15388/Informatica.2018.155
  
• [2129] Y. Dong, Y. Liu, H. Liang, F. Chiclana, E. Herrera-Viedma. Strategic weight manipulation in multiple attribute decision making. Omega: The International Journal of Management Science 75 (2018) 154–164. doi: 10.1016/j.omega.2017.02.008
  
• [2136] O. Taylan , M.R. Kabli, C. Porcel, E. Herrera-Viedma. Using consensus tools and fuzzy linguistic modelling for constructor selection. Int. J. of Fuzzy Systems, 2018, Vol. 20, Issue 4, pp 1267–1281..
  
• [2142] X. Tian, Z. Xu, J. Gu, E. Herrera-Viedma. How to select a promising enterprise for venture capitalists with prospect theory under intuitionistic fuzzy circumstance?. Applied Soft Computing, 67 (2018) 756-763.. doi: 10.1016/j.asoc.2017.04.027
  
• [2148] J. Bernabé-Moreno, A. Tejeda-Lorente, C. Porcel, E. Herrera-Viedma. Leveraging localized social media insights for early warning systems. International Journal of Information Technology and Decision Making (IJITDM) 17:1 (2018) 357-385. doi: 10.1142/S0219622017400016
  
• [2434] R. Hernández-Linares, S. Sarkar, M.J. Cobo. Inspecting an Achilles heel: A quantitative analysis of fifty years of attempts to define family business. Scientometrics, 115:2 (2018) 929–951. doi: 10.1007/s11192-018-2702-1
  
• [2210] C. Campomanes-Álvarez, O. Ibáñez, O. Cordón, C. Wilkinson. A Fuzzy Hierarchical Decision Support Framework for Craniofacial Superimposition. Information Fusion 39 (2018) 25–40. doi: 10.1016/j.inffus.2017.03.004
  
• [2279] F.J. Baldán, S.Ramirez-Gallego, C.Bergmeir, F.Herrera, J.M.Benitez-Sanchez. A Forecasting Methodology for Workload Forecasting in Cloud Systems. IEEE Transactions on Cloud Computing 6:4 (2018) 929-941. doi: 10.1109/TCC.2016.2586064
  COMPLEMENTARY MATERIAL to the paper
  
  
• [2299] R. Montes, A.M. Sánchez, P. Villar, F. Herrera. Teranga Go!: Carpooling Collaborative Consumption Community with multi-criteria hesitant fuzzy linguistic term set opinions to build confidence and trust. Applied Soft Computing. Volume 67, June 2018, Pages 941-952. doi: 10.1016/j.asoc.2017.05.039
  
• [2300] F. Chiclana, F. Mata, L.G. Pérez, E. Herrera-Viedma. Type-1 OWA unbalanced fuzzy linguistic aggregation methodology. Application to eurobonds credit risk evaluation. Int. J. of Intelligent Syst. 33:5, 2018, 1071-1088..
  
• [2408] J. Montero, M.J. Cobo, M. Gutiérrez-Salcedo, F. Segado and E. Herrera-Viedma. A Science Mapping Analysis of Communication WoS Subject Category (1980-2013). Comunicar, 55:16 (2018) 81-91. doi: 10.3916/C55-2018-08
  
• [2309] M. Gonzalez, C. Bergmeir, I. Triguero, Y. Rodriguez, J.M. Benitez. Self-labeling techniques for semi-supervised time series classification: an empirical study. Knowledge and Information Systems, 55 (2), 493-528. doi: 10.1007/s10115-017-1090-9
  
• [2314] N. Capuano, F. Chiclana, H. Fujita, E. Herrera-Viedma, V. Loia. Fuzzy group decision making with incomplete information guided by social influence. EEE Trans. On Fuzzy Systems 26(3) (2018) 1704-1718.. doi: 10.1109/TFUZZ.2017.2744605
  
• [2315] B. Farhadinia, E. Herrera-Viedma. Entropy measures for extended hesitant fuzzy linguistic term sets using the concept of interval-transformed hesitant fuzzy elements. Int. J. of Fuzzy Systems, 2018. Volume 20, Issue 7, pp 2122–2134. Doi: 10.1007/s40815-017-0379-x.
  
• [2319] S. Ramírez-Gallego, S. García, J.M. Benítez, F. Herrera. A distributed evolutionary multivariate discretizer for Big Data processing on Apache Spark. Swarm and Evolutionary Computation 38 (2018) 240-250. doi: 10.1016/j.swevo.2017.08.005
  
• [2320] J. Wu, F. Chiclana, H. Fujita, E. Herrera-Viedma. A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust. Information Fusion, 41 (2018) 232-242. doi: 10.1016/j.inffus.2017.09.012
  
• [2324] S. Vluymans, A. Fernandez, C. Cornelis, Y. Saeys, F. Herrera. Dynamic Affinity-based Classification of Multi-Class Imbalanced Data with One-vs-One Decomposition: a Fuzzy Rough Set Approach. Knowledge and Information Systems 56:1 (2018) 55–84. doi: 10.1007/s10115-017-1126-1
  
• [2331] M. Gutiérrez-Salcedo, M.A. Martínez, J.A. Moral-Muñoz, E. Herrera-Viedma, M.J. Cobo. Some bibliometric procedures for analyzing and evaluating research fields. Applied Intelligence, 48:5 (2018) 1275–1287.. doi: 10.1007/s10489-017-1105-y
  
• [2337] R.A. Carrasco-González, M.F. Blasco, J. García-Madariaga, A. Pedreño-Santos, E. Herrera-Viedma. A model to obtain a SERVPERF scale evaluation of the CRM customer complaints: An application to the 4G telecommunications sector. Technological and Economic Development of Economy, 2018 Vol. 24 Issue 4: 1606–1629.. doi: 10.3846/tede.2018.5080
  
• [2338] S. Ramírez-Gallego, A. Fernández, S. García, M. Chen, F. Herrera. Big Data: Tutorial and Guidelines on Information and Process Fusion for Analytics Algorithms with MapReduce. Information Fusion 42 (2018) 51-61. doi: 10.1016/j.inffus.2017.10.001
  
• [2339] R. Rekik, I. Kallel, J. Casillas, A.M. Alimi. Assessing web sites quality: a systematic literature review by text and association rules mining. International Journal of Information Management 38:1 (2018) 201-216. doi: 10.1016/j.ijinfomgt.2017.06.007
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• [2345] F. Padillo, J.M. Luna, F. Herrera, S. Ventura. Mining Association Rules on Big Data through MapReduce Genetic Programming. Integrated Computer-Aided Engineering.
  
• [2364] D. Peralta, I. Triguero, S. García, Y. Saeys, J.M. Benítez, F. Herrera. On the use of convolutional neural networks for robust classiffication of multiple fingerprint captures. International Journal of Intelligent Systems 33:1 (2018) 213–230. doi: 10.1002/int.21948
  
• [2365] C.J. Carmona, M.J. del Jesus, F. Herrera. A Unifying Analysis for the Supervised Descriptive Rule Discovery via the Weighted Relative Accuracy. Knowledge-Based Systems (2017). doi: 10.1016/j.knosys.2017.10.015
  
• [2372] R. Olmos, S. Tabik, F. Herrera. Automatic Handgun Detection Alarm in Videos Using Deep Learning. Neurocomputing 275, 66-72 (2018).. doi: 10.1016/j.neucom.2017.05.012
  
• [2378] W. Wang, S. Laengle, J.M. Merigó, D. Yu, E. Herrera-Viedma, M.J. Cobo, B. Bouchon-Meunier. A bibliometric analysis of the first twenty-five years of the International Journal of Uncertainty, Fuzziness and Knowledge-based Systems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 26, No. 2 (2018) 169–193. doi: 10.1142/S0218488518500095
  
• [2383] J. Luengo, S.O. Shim, S. Alshomrani, A. Altalhi, F. Herrera. CNC-NOS: Class Noise Cleaning by Ensemble Filtering and Noise Scoring. Knowledge-Based Systems 140 (2018) 27-49. doi: 10.1016/j.knosys.2017.10.026
  OMPLEMENTARY MATERIAL to the paper: datasets, experimental results
  
  
• [2385] M.J. del Moral, F. Chiclana, J.M. Tapia, E. Herrera-Viedma. A Comparative Study on Consensus Measures in Group Decision Making. Int. J. of Intelligent Systems, 33(8), 1624-1638, 2018.. doi: https://doi.org/10.1002/int.21954
  
• [2386] H. Liao, Z. Xu, E. Herrera-Viedma, F. Herrera. Hesitant fuzzy linguistic term set and its application in decision making: A state-of-the-art survey. Int. J. of Fuzzy Systems, 2018, Volume 20, Issue 7, pp 2084–2110.. doi: 10.1007/s40815-017-0432-9
  
• [2403] M. J. Del Moral, J. M. Tapia Garcia, F. Chiclana, A. Al-Hmouz, E. Herrera-Viedma. An analysis of consensus approaches based on different concepts of coincidence. J. of Intelligent and Fuzzy Systems, 34 (2018) 2247–2259. doi: 10.3233/jifs-171282
  
• [2406] M. V. Ciasullo, G. Fenza, V. Loia, F. Orciuoli, O. Troisi, E. Herrera-Viedma. Business Process Outsourcing Enhanced by Fuzzy Linguistic Consensus Model. Applied Soft Computing, 2018, 64 (2018) 436–444. doi: 10.1016/j.asoc.2017.12.020
  
• [2409] C. Koulamas, A.P. Kalogeras, R. Pacheco-Torres, J. Casillas, L. Ferrarini. Suitability analysis of modeling and assessment approaches in energy efficiency in buildings. Energy and Buildings 158 (2018) 1662-1682. doi: 10.1016/j.enbuild.2017.12.002
  
• [2410] E. Ruiz, J. Casillas. Adaptive fuzzy partitions for evolving association rules in big data stream. International Journal of Approximate Reasoning 93 (2018) 463-486. doi: 10.1016/j.ijar.2017.11.014
  
• [2411] M.P. Rodríguez Bolivar, L. Alcaide Muñoz, M.J. Cobo. Analyzing the scientific evolution and impact of e-participation research in JCR journals using science mapping. International Journal of Information Management, 40 (2018) 111-119, 2018. doi: 10.1016/j.ijinfomgt.2017.12.011
  
• [2412] A. Kaklauskas, E. Herrera-Viedma, E. K. Zavadskas, I. Ubarte, V. Echenique, A. Kuzminske, A. Binkyte. Multiple criteria analysis of environmental sustainability and quality of life in post-Soviet states. Ecological Indicators, 89 (2018) 781-807.. doi: 10.1016/j.ecolind.2017.12.070
  
• [2414] F.J. Cabrerizo, J.A. Morente-Molinera, W. Pedrycz, A. Taghavi, E. Herrera-Viedma. Granulating linguistic information in decision making under consensus and consistency. Expert Systems With Applications 99 (2018) 83-92. doi: 10.1016/j.eswa.2018.01.030
  
• [2422] R. Alcalá, M.J. Gacto, J. Alcalá-Fdez. Evolutionary data mining and applications: A revision on the most cited papers from the last 10 years (2007-2017). Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery 8:2 (2018) 1-17. doi: 10.1002/widm.1239
  
• [2425] J. Bernabé-Moreno, A. Tejeda-Lorente, C. Porcel, H. Fujita, E. Herrera-Viedma. Quantifying the emotional impact of events on locations with Social Media. Knowledge-based Systems, 146, (2018), 44-57. doi: 10.1016/j.knosys.2018.01.029
  
• [2427] A. Cid-López, Miguel J. Hornos, R. A. Carrasco-González, E. Herrera-Viedma. Prioritization of the launch of ict products and services through linguistic multi-criteria decision-making. Technological and Economic Development of Economy, 2018 Volume 24 Issue 3: 1231–1257. doi: 10.3846/tede.2018.1423
  
• [2428] P. Lázaro-Rodríguez, J. López-Gijón, S. Alonso, M. J. Martínez-Sánchez, E. Herrera-Viedma. Secaba-Rank: una herramienta online para analizar y evaluar las bibliotecas. El profesional de la información, v. 27, n. 2, pp. 278-288. doi: doi.org/10.3145/epi.2018.mar.06
  
• [2429] P. Lázaro-Rodríguez, J. López-Gijón, E. Herrera-Viedma. Visibilidad de las bibliotecas públicas y la lectura en medios de comunicación españoles frente a otros hechos de la cultura y relación con su uso: medidas para su mayor promoción y difusión.. BiD: textos universitaris de biblioteconomia i documentació, n. 40 (junio)..
  
• [2430] P. Lázaro-Rodríguez, P. Vakkari. Modelizando el uso de las bibliotecas públicas a través de sus características: estudio comparativo entre España y Finlandia para los préstamos y las visitas. Revista Española de Documentación Científica, 41 (4): e216. doi: 10.3989/redc.2018.4.1544
  
• [2431] A. Fernandez, S. Garcia, N.V. Chawla, F. Herrera. SMOTE for Learning from Imbalanced Data: Progress and Challenges. Marking the 15-year Anniversary. Journal of Artificial Intelligence Research 61 (2018) 863-905. doi: 10.1613/jair.1.11192
  
• [2435] J.A. Moral-Muñoz, M. Arroyo-Morales, E. Herrera-Viedma, M.J. Cobo. An Overview of Thematic Evolution of Physical Therapy Research Area from 1951 to 2013. Frontiers in Research Metrics and Analytics, 3:13 (2018). doi: 10.3389/frma.2018.00013
  
• [2436] J.A. Morente-Molinera, G. Kou, Y. Peng, C. Torres-Albero, E. Herrera-Viedma. Analysing discussions in social networks using group decision making methods and sentiment analysis. Information Sciences, 447 (2018) 157-168. doi: 10.1016/j.ins.2018.03.020
  
• [2437] N. Capuano, F. Chiclana, E. Herrera-Viedma, H. Fujita, V. Loia. Fuzzy Rankings for Preferences Modeling in Group Decision Making. Int. Journal of Intelligent Systems, 33 (7) (2018) 1555-1570. doi: 10.1002/int.21997
  
• [2438] D. Torres-Salinas, N. Robinson-García, E. Herrera-Viedma y E. Jiménez-Contreras. Consideraciones metodológicas sobre el uso del Impacto Normalizado en las convocatorias Severo Ochoa y María de Maetzu. El Profesional de la Información, v. 27, n. 2, pp. 367-374. doi: 10.3145/epi.2018.mar.15
  
• [2440] V. Perez-Cabezas, C. Ruiz-Molinero, I. Carmona-Barrientos, E. Herrera-Viedma, M.J. Cobo, J.A. Moral-Muñoz. Highly cited papers in Rheumatology: Identification and conceptual analysis. Scientometrics 116:(2018) 555-568. doi: 10.1007/s11192-018-2712-z
  
• [2443] D. Lucena-Antón, I. Rosety-Rodríguez, J.A. Moral-Muñoz. Effects of a Hippotherapy Intervention on Muscle Spasticity in Children with Cerebral Palsy: A Randomized Controlled Trial. Complementary Therapies in Clinical Practice 31 (2018) 188-192. doi: 10.1016/j.ctcp.2018.02.013
  
• [2444] Y. Dong, S. Zhao, H. Zhang, F. Chiclana, E. Herrera-Viedma. A self-management mechanism for non-cooperative behaviors in large-scale group consensus reaching processes. IEEE Trans. On Fuzzy Systems, Volume: 26 , Issue: 6 , Dec. 2018, pp. 3276 – 3288. doi: 10.1109/TFUZZ.2018.2818078
  
• [2445] A. González-Briones, J. Prieto, F. De La Prieta, E. Herrera-Viedma, J.M. Corchado. Energy Optimization Using a Case-Based Reasoning Strategy. Sensors 18:3 (2018) 865. doi: 10.3390/s18030865
  
• [2446] Y. Xu, Q. Wang, F.J. Cabrerizo, E. Herrera-Viedma. Methods to improve the ordinal and multiplicative consistency for fuzzy reciprocal preference relations. Applied Soft Computing 67 (2018) 479-493. doi: 10.1016/j.asoc.2018.03.034
  
• [2448] J.A. Morente-Molinera, G. Kou, I.J. Pérez, K. Samuylov, A. Selamat, E. Herrera-Viedma. A group decision making support system for the Web: how to work in environments with a high number of participants and alternatives. Applied Soft Computing, 68 (2018) 191-201. doi: 10.1016/j.asoc.2018.03.047
  
• [2449] D.G. Cañizares, A. Fernandez, F. Herrera, A. Antunes, R. Molina-Ruiz, G. Agüero-Chapin. Surveying Alignment-free Features for Ortholog Detection in Related Yeast Proteomes by using Supervised Big Data Classifiers. BMC Bioinformatics 19:166 (2018) 1-17. doi: 10.1186/s12859-018-2148-8
  
• [2460] C. Zhang, Xi. Wu, D. Wu, H. Liao, L. Luo, E. Herrera-Viedma. An intuitionistic multiplicative ORESTE method for patients’ prioritization of hospitalization. International Journal of Environmental Research and Public Health (ISSN 1660-4601). vol. 15, no. 4: 777, 2018. doi: 10.3390/ijerph15040777
  
• [2461] A. Santisteban-Espejo, F. Campos, L. Martin-Piedra, D. Durand-Herrera, J.A. Moral-Muñoz, A. Campos, M.A. Martin-Piedra. Global tissue engineering trends: A scientometric and evolutive study. Tissue Ingineering 24:19-20 (2018) 1504-1517. doi: 10.1089/ten.TEA.2018.0007
  
• [2462] D. Martín, M. Martínez-Ballesteros, D. García-Gil, J. Alcalá-Fdez, J.C. Riquelme-Santos, F. Herrera. MRQAR: a generic MapReduce framework to discover Quantitative Association Rules in Big Data problems. Knowledge-Based Systems 153 (2018) 176-192. doi: 10.1016/j.knosys.2018.04.037
  
• [2463] D. Molina, A. LaTorre, F. Herrera. An Insight into Bio-inspired and Evolutionary Algorithms for Global Optimization: Review, Analysis, and Lessons Learnt over a Decade of Competitions. Cognitive Computation (2018) 10:4, 517-544. doi: 10.1007/s12559-018-9554-0
  
• [2464] J. Redfern, M.J. Cobo, E. Herrera-Viedma. Editorial: Mapping microbiology with scientometrics - help provide a clearer vision of microbiology research around the globe. FEMS Microbiology Letters, 365:9, (2018), fny061. doi: 10.1093/femsle/fny061
  
• [2469] J.A. Moral-Muñoz, M. Arroyo-Morales, B.F. Piper, A.I. Cuesta-Vargas, L. Díaz-Rodríguez, W.C.S. Cho, E. Herrera-Viedma, M.J. Cobo. Thematic Trends in Complementary and Alternative Medicine Applied in Cancer-Related Symptoms. Journal of Data and Information Science 3:2 (2018) 1-19. doi: 10.2478/jdis-2018-0006
  
• [2466] I.J. Perez, F.J. Cabrerizo, S. Alonso, Y. C. Dong, F. Chiclana, E. Herrera-Viedma. On Dynamic Consensus Processes in Group Decision Making Problems. Information Sciences 459 (2018) 20-35. doi: 10.1016/j.ins.2018.05.017
  
• [2467] M. Tang, H. Liao, Z. Wan, E. Herrera-Viedma, M. A. Rosen. Ten Years of Sustainability (2009 to 2018): A Bibliometric Overview. Sustainability, vol. 10, no. 5: 1655, 2018. doi: 10.3390/su10051655
  
• [2468] J.A. Moral-Muñoz, B. Esteban-Moreno, E. Herrera-Viedma, M.J. Cobo, I.J. Pérez. Smartphone applications to perform body balance assessment: A standardized review. Journal of Medical Systems 42:119 (2018) 1-8. doi: 10.1007/s10916-018-0970-1
  
• [2471] Y. Dong, Q. Zha, H. Zhang, G. Kou, H. Fujita, F. Chiclana, E. Herrera-Viedma. Consensus Reaching in Social Network Group Decision Making: Research Paradigms and Challenges. Knowledge-Based Systems, Volume 162, 15 December 2018, Pages 3-13..
  
• [2472] A. Yazidis, T.M Jonassen, E. Herrera-Viedma. An Aggregation Approach for Solving the Non-linear Fractional Equality Knapsack Problem. Expert Systems with Applications, Volume 110, 15 November 2018, Pages 323-334..
  
• [2475] A. Salazar, H. de Sola, I. Failde, J.A. Moral-Muñoz. Measuring the quality of mobile applications for the management of pain: a standardised review using the mobile app rating scale (MARS). JMIR mHealth and uHealth 6:10 (2018) e10718. doi: 10.2196/10718
  
• [2476] C. Porcel, A. Ching-Lopez, G. LeFranc, V. Loia, E. Herrera-Viedma. Sharing Notes: An academic social network based on a personalized fuzzy linguistic recommender system. Engineering Applications of Artificial Intelligence, Vol. 75, 1-10, 2018.. doi: 10.1016/j.engappai.2018.07.007
  
• [2480] J.F. García-Henares, J.A. Moral-Muñoz, A. Salazar, E. del Pozo. Effects of ketamine on postoperative pain after remifentanil-based anesthesia for major and minor surgery in adults: A systematic review and meta-analysis. Frontiers in Pharmacology 9 (2018) 921. doi: 10.3389/fphar.2018.00921
  
• [2481] E. R. Nuñez-Valdez, D. Quintana, R. González-Crespo, P. Isasi, E. Herrera-Viedma. A recommender system based on implicit feedback for selective dissemination of eBooks. Information Science. Vol. 467 (2018) 87-98. doi: 10.1016/j.ins.2018.07.068
  
• [2486] I. Cordon, S. Garcia, A. Fernandez, F. Herrera. imbalance: Oversampling Algorithms for Imbalanced Classification in R. Knowledge-Based Systems 161 (2018) 329-341. doi: 10.1016/j.knosys.2018.07.035
  
• [2489] Z. Rezaei, A. Selamat, A. Taki, M. S. M. Rahim, M. R. A. Kadir, M. Penhaker, O. Krejcar, K. Kuca, E. Herrera-Viedma, H. Fujita. Thin Cap Fibroatheroma Detection in Virtual Histology Images Using Geometric and Texture Features. Applied Sciences 8:9 (2018) 1632. doi: 10.3390/app8091632
  
• [2491] S. Kublera, W. Derigenta, A. Voisina, J. Robert, Y. Traon, E. Herrera-Viedma. Measuring Inconsistency and Deriving Priorities from Fuzzy Pairwise Comparison Matrices using the Knowledge-based Consistency Index. Knowledge Based Systems, Knowledge-Based Systems 162 (2018) 147–160. doi: 10.1016/j.knosys.2018.09.015
  
• [2497] J.A. Moral-Muñoz, D. Lucena-Antón, V. Pérez-Cabezas, I. Carmona-Barrientos, G. González-Medina, C. Ruiz-Molinero. Highly Cited Papers in Microbiology: Identification and Conceptual Analysis. FEMS Microbiology Letters 365:20 (2018) fny230. doi: 10.1093/femsle/fny230
  
• [2505] J.M. Soto-Hidalgo, J.M. Alonso, G. Acampora, J. Alcalá-Fdez. JFML: A Java Library to Design Fuzzy Logic Systems According to the IEEE Std 1855-2016. IEEE Access 6 (2018) 54952-54964. doi: 10.1109/ACCESS.2018.2872777
  
• [2504] M. Bustamante, A. Rienzo, R. Osorio, E. Lefranc, M. Duarte, E. Herrera-Viedma, G. Lefranc. Algorithm for processing Mammography: detection of microcalcifications. IEEE Latin America Transactions 16:9 (2018) 2460-2466. doi: 10.1109/TLA.2018.8789569
  
• [2515] A. Cid-López, M. J. Hornos, R. A. Carrasco-González, E. Herrera-Viedma. Prioritization of the launch of ICT products and services through linguistic multi-criteria decision-making. Technological and Economic Development of Economy 24:3 (2018) 1231-1257. doi: 10.3846/tede.2018.1423
  
• [2525] H. Baier-Fuentes, J. Cascón-Katchadourian, M.A. Sánchez, E. Herrera-Viedma, J.M. Merigó. A Bibliometric Overview of the International Journal of Interactive Multimedia and Artificial Intelligence. International Journal of Interactive Multimedia and Artificial Intelligence. 2018;5(3) pp.9-16. doi: 10.9781/ijimai.2018.12.003
  
• [2569] A. Valdivia, M.V. Luzón, E. Cambria, F. Herrera. Consensus vote models for detecting and filtering neutrality in sentiment analysis. Information Fusion 44 (2018) 126-135. doi: 10.1016/j.inffus.2018.03.007
  
• [2570] Z-L. Zhang, X-G. Luo, S. González, S. García, F. Herrera. DRCW-ASEG: One-versus-One distance-based relative competence weighting with adaptive synthetic example generation for multi-class imbalanced datasets. Neurocomputing 285 (2018) 176-187. doi: 10.1016/j.neucom.2018.01.039
  
• [2576] M.J. Basgall, W. Hasperué, M. Naiouf, A. Fernandez, F. Herrera. SMOTE-BD: An Exact and Scalable Oversampling Method for Imbalanced Classification in Big Data. Journal of Computer Science & Technology 18:3 (2018) 203-209.
  
• [2580] D. García-Gil, S. Ramírez-Gallego, S. García, F. Herrera. Principal Components Analysis Random Discretization Ensemble for Big Data. Knowledge-Based Systems, 150, 2018, 166-174. doi: 10.1016/j.knosys.2018.03.012
  
• [2584] D. Charte, F. Charte, S. García, F. Herrera. A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations. Progress in Artificial Intelligence, 2018, 1-14. doi: 10.1007/s13748-018-00167-7
  
• [2585] S. Ramírez-Gallego, S. García, F. Herrera. Online entropy-based discretization for data streaming classification. Future Generation Computer Systems 86, 2018, 59-70. doi: 10.1016/j.future.2018.03.008
  
• [2586] S. García, ZL. Zhang, A. Altalhi, S. Alshomrani, F. Herrera. Dynamic ensemble selection for multi-class imbalanced datasets. Information Sciences 445, 2018, 22-37. doi: 10.1016/j.ins.2018.03.002
  
• [2589] B. Krawczyk, I. Triguero, S. García, M. Wozniak, F. Herrera. Instance reduction for one-class classification. Knowledge and Information Systems, 2018, 1-28. doi: 10.1007/s10115-018-1220-z
  
• [2592] A. Rosales-Perez, S. García, H. Terashima-Marin, CAC. Coello, F. Herrera. MC2ESVM: Multiclass Classification Based on Cooperative Evolution of Support Vector Machines. IEEE Computational Intelligence Magazine 13 (2), 2018, 18-29. doi: 10.1109/MCI.2018.2806997
  
• [2593] D. Charte, F. Charte, S. García, M. J. del Jesus, F. Herrera. A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines. Information Fusion 44, 2019, 78–96. doi: 10.1016/j.inffus.2017.12.007
  
• [2598] A. Sánchez-Fernández, F.J. Baldán, G. I. Sainz-Palmero, J. M. Benítez, M. J. Fuente. Fault detection based on time series modeling and multivariate statistical process control. Chemometrics and Intelligent Laboratory Systems 182 (2018) 57-69. doi: 10.1016/j.chemolab.2018.08.003
  
• [2604] A. Valsecchi, S. Damas, O. Cordón. A robust and efficient method for skull-face overlay in computerized craniofacial superimposition. IEEE Transactions on Information Forensics and Security 13:8 (2018) 1960-1974. doi: 10.1109/TIFS.2018.2806939
  
• [2605] E. Bermejo, M. Chica, S. Damas, S. Salcedo, O. Cordón. Coral reef optimization with substrate layers for medical image registration. Swarm and Evolutionary Computation 42 (2018) 138-159. doi: 10.1016/j.swevo.2018.03.003
  
• [2621] C. Zuheros, C.-C. Li, F.J. Cabrerizo, Y. Dong, E. Herrera-Viedma, F. Herrera. Computing with words: Revisiting the qualitative scale. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26:Suppl. 2 (2018) 127-143. doi: 10.1142/S0218488518400147
  
• [2625] 64. H. Zhang, Y. Dong, E. Herrera-Viedma. Consensus building for the heterogeneous large-scale GDM with the individual concerns and satisfactions. IEEE Trans. On Fuzzy Systems. 26:2 (2018) 884-898. doi: 10.1109/TFUZZ.2017.2697403
  
• [2626] M. Victor, M. Mondragon, V. Garcia-Diaz, R. González-Crespo, C. Porcel, E. Herrera-Viedma. Adaptive contents for Interactive TV guided by machine learning based on predictive sentiment analysis of data. Soft Computing, 22:8 (2018) 1-22. doi: 10.1007/s00500-017-2530-x
  
• [2627] S. Tabik, M. Peemen, L. F. Romero. A tuning approach for iterative multiple 3d stencil pipeline on GPUs: Anisotropic Nonlinear Diffusion algorithm as case study. The Journal of Supercomputing 74:4 (2018) 1580-1608. doi: 10.1007/s11227-017-2184-6
  
• [2630] W. Ding, I. Triguero, CT. Lin. Coevolutionary Fuzzy Attribute Order Reduction With Complete Attribute-Value Space Tree. IEEE Transactions on Emerging Topics in Computational Intelligence. doi: 10.1109/TETCI.2018.2869919
  
• [2643] C. Li, R. M. Rodríguez, F. Herrera, L. Martínez, Y. Dong. Consistency of hesitant fuzzy linguistic preference relations: An interval consistency index. Information Sciences, 432 (2018) 347-361. doi: 10.1016/j.ins.2017.12.018
  
• [2644] S. Vluymans, C. Cornelis, F. Herrera, Y. Saeys. Multi-Label Classification using a Fuzzy Rough Neighborhood Consensus. Information Sciences, vol. 433-434 (2018), 96-114.. doi: 10.1016/j.ins.2017.12.034
  
• [2645] M. Chen, F. Herrera, K. Hwang. Cognitive Computing: Human-Centered Computing with Cognitive Intelligence on Clouds. IEEE Access, 6 (2018) 19774 – 19783. doi: 10.1109/ACCESS.2018.2791469
  
• [2646] R. M. Rodríguez, Y. Xu, L. Martínez, F. Herrera. Exploring Consistency for Hesitant Preference Relations in Decision Making: Discussing Concepts, Meaning and Taxonomy.. Journal of multiple-valued logic and soft computing, 30:2-3 (2018) 129-154.
  
• [2647] G. Acampora, F. Herrera, G. Tortora, A. Vitiello. A multi-objective evolutionary approach to training set selection for support vector machine. Knowledge-Based Systems, 147 (2018) 94-108.. doi: 10.1016/j.knosys.2018.02.022
  
• [2648] I. Chaturvedi, E. Cambria, R. E. Welsch, F. Herrera. Distinguishing Between Facts and Opinions for Sentiment Analysis: Survey and Challenges. Information Fusion, 44 (2018) 65-77.. doi: 10.1016/j.inffus.2017.12.006
  
• [2649] F. Charte, A. J Rivera, D. Charte, M. J. del Jesus, F Herrera. Tips, guidelines and tools for managing multi-label datasets: the MLDR. datasets R package and the Cometa data repository. Neurocomputing, 289 (2018) 68-85. doi: 10.1016/j.neucom.2018.02.011
  
• [2650] X. Gou, Z. Xu, F. Herrera. Consensus Reaching Process for Large-scale Group Decision Making with Double Hierarchy Hesitant Fuzzy Linguistic Preference Relations. Knowledge-Based Systems, 157 (2018) 20-33. doi: 10.1016/j.knosys.2018.05.008
  
• [2653] B. Krawczyk, M. Galar, M. Wozniak, H. Bustince, F. Herrera. Dynamic ensemble selection for multi-class classification with one class classifiers. Pattern Recognition, 83 (2018) 34-51.. doi: 10.1016/j.patcog.2018.05.015
  
• [2654] A. Roldan, C. Roldán, F. Herrera.. On a new methodology for ranking fuzzy numbers and its application to real economic data. Fuzzy Sets and Systems, 353 (2018) 86-110. doi: 10.1016/j.fss.2018.04.003
  
• [2655] H. Liao, X. Wu, X. Liang, J.-B. Yang, D.-L. Xu, F. Herrera. A continuous interval-valued linguistic ORESTE method for multi-criteria group decision making. Knowledge-Based Systems, 153 (2018) 65-77. doi: 10.1016/j.knosys.2018.04.022
  
• [2656] C. Li, R. M. Rodríguez, L. Martínez, Y. Dong, F. Herrera. Personalized individual semantics based on consistency in hesitant linguistic group decision making with comparative linguistic expressions. Knowledge-Based Systems, 145 (2018), 156-165.. doi: 10.1016/j.knosys.2018.01.011
  
• [2657] H. C. Liao, X. M. Mi, Z. S. Xu, J. P. Xu, F. Herrera. Intuitionistic fuzzy analytic network process. IEEE Transactions on Fuzzy Systems, 26:5 (2018), 2578-2590. doi: 10.1109/TFUZZ.2017.2788881
  
• [2658] X. Wu, H. Liao, Z. Xu, A. Hafezalkotob, F. Herrera. Probabilistic Linguistic MULTIMOORA: A Multi-Criteria Decision Making Method Based on the Probabilistic Linguistic Expectation Function and the Improved Borda Rule. IEEE Transactions on Fuzzy Systems, 26:6 (2018), 3688-3702. doi: 10.1109/TFUZZ.2018.2843330
  
• [2659] H Liao, XL Wu, XD Liang, J. P. Xu, F Herrera. A new hesitant fuzzy linguistic oreste method for hybrid multicriteria decision making. IEEE Transactions on Fuzzy Systems, 26:6 (2018), 3793-3807. doi: 10.1109/TFUZZ.2018.2849368
  
• [2660] X. Gou, Z. Xu, H. Liao, F. Herrera. Multiple criteria decision making based on distance and similarity measures under double hierarchy hesitant fuzzy linguistic environment. Computers & Industrial Engineering, 126 (2018) 516-530. doi: 10.1016/j.cie.2018.10.020
  
• [2661] Z. Fu, X. Wu, H. Liao, F. Herrera. Underground mining method selection with the hesitant fuzzy linguistic gained and lost dominance score method. IEEE Access, 6 (2018), 66442-66458. doi: 10.1109/ACCESS.2018.2878784
  
• [2779] J. Albadán-Romero, P. Gaona-García, G. Rolong-Agudelo, C. Montenegro-Marin. R. Gonzalez-Crespo, E. Herrera Viedma. Fuzzy Logic Models for Non-Programmed Decision-Making in Personnel Selection Processes Based on Gamification. Informatica, vol. 29, no. 1, pp. 1-20, 2018..
  
• [2814] J. Cascón-Katchadourian, A.A. Ruíz-Rodríguez, J. Alberich. Uses and applications of georeferencing and geolocation in old cartographic and photographic document management. El profesional de la información 27:1 (2018) 202-212. doi: 10.3145/epi.2018.ene.19
  
• [2815] J. Cascón-Katchadourian, A.A. Ruíz-Rodríguez, J. Alberich. Revisión, análisis y evaluación de sistemas para la gestión de activos multimedia en organizaciones. Revista Española de Documentación Científica 41:1 (2018) e196. doi: 10.3989/redc.2018.1.1481
  
• [2816] J. Cascón-Katchadourian, A.A. Ruíz-Rodríguez, A. Quesada-Román. Georreferenciación y publicación web de cartografía antigua en sistemas de información geográficos: requisitos para su evaluación y estudio de caso. Revista General de Información y Documentación 28:1 (2018) 193-212. doi: 10.5209/RGID.60810
  

2017 (68)

• [2105] F. J. Rodriguez , F. Glover, C. García-Martínez, R. Martí, M. Lozano. GRASP with exterior path-relinking and restricted local search for the multidimensional two-way number partitioning problem. Computers & Operations Research 78 (2017) 243-254. doi: 10.1016/j.cor.2016.09.005
  
• [1945] R. A. Carrasco, J. Sánchez-Fernández, F. Muñoz-Leiva, M. F. Blasco, E. Herrera-Viedma. Evaluation of the Hotels E-Services Quality Under the User's Experience. Soft Computing 21:4 (2017) 995-1011. doi: 10.1007/s00500-015-1832-0
  
• [1970] F.J. Cabrerizo, J. López-Gijón, M.A. Martínez, J.A. Morente-Molinera, E. Herrera-Viedma. A fuzzy linguistic extended libqual+ model to assess service quality in academic libraries. International Journal of Information Technology & Decision Making 16:1 (2017) 225-244. doi: 10.1142/S0219622015500406
  
• [1994] F.J. Cabrerizo, R. Al-Hmouz, A. Morfeq, A.S. Balamash, M.A. Martínez, E. Herrera-Viedma. Soft consensus measures in group decision making using unbalanced fuzzy linguistic information. Soft Computing 21:11 (2017) 3037-3050. doi: 10.1007/s00500-015-1989-6
  
• [2307] J. Alcalá-Fdez, R. Alcalá, S. González, Y. Nojima, S. García. Evolutionary Fuzzy Rule-Based Methods for Monotonic Classification. IEEE Transactions on Fuzzy Systems 25:6 (2017) 1376-1390. doi: 10.1109/TFUZZ.2017.2718491
  
• [2086] A. Fernandez, S. Río, F. Herrera. Fuzzy Rule Based Classification Systems for Big Data with MapReduce: Granularity Analysis. Advances in Data Analysis and Classification 11 (2017) 711-730. doi: 10.1007/s11634-016-0260-z
  
• [2089] J. Maillo, S. Ramírez-Gallego, I. Triguero, F. Herrera. kNN-IS: An Iterative Spark-based design of the k-Nearest Neighbors classifier for big data. Knowledge-Based Systems 117 (2017) 3-15. doi: 10.1016/j.knosys.2016.06.012
  
• [2091] J.A. Morente-Molinera, J. Mezei, C. Carlsson, E. Herrera-Viedma. Improving supervised learning classification methods using multi-granular linguistic modelling and fuzzy entropy. IEEE Transactions on Fuzzy Systems 25:5 (2017) 1078-1089. doi: 10.1109/TFUZZ.2016.2594275
  
• [2096] S. Ramírez-Gallego, I. Lastra, D. Martínez-Rego, V. Bolón-Canedo, J.M. Benítez, F. Herrera, A. Alonso-Betanzos. Fast-mRMR: Fast minimum Redundancy Maximum Relevance algorithm for high dimensional big data. International Journal of Intelligent Systems 32:2 (2017) 134-152. doi: 10.1002/int.21833
  
• [2100] Li, C-C., Y. Dong, F. Herrera, E. Herrera-Viedma, and L. Martínez. Personalized individual semantics in Computing with Words for supporting linguistic Group Decision Making. An Application on Consensus reaching. Information Fusion 33:1 (2017) 29-40.
  
• [2110] W. Liu, Y. Dong, F. Chiclana, F.J. Cabrerizo, E. Herrera-Viedma. Group decision-making based on heterogeneous preference relations with self-confidence. Fuzzy Optimization and Decision Making 16:4 (2017) 429-447. doi: 10.1007/s10700-016-9254-8
  
• [2111] M. Lozano, C. García-Martínez, F. J. Rodriguez, H. Trujillo. Optimizing Network Attacks by Artificial Bee Colony. Information Sciences 377 (2017) 30-50. doi: 10.1016/j.ins.2016.10.014
  
• [2113] M. Galar, A. Fernandez, E. Barrenechea, H. Bustince, F. Herrera. NMC: Nearest Matrix Classification – A new combination model for pruning One-vs-One ensembles by transforming the aggregation problem. Information Fusion 36 (2017) 26–51. doi: 10.1016/j.inffus.2016.11.004
  
• [2117] J. Wu, F. Chiclana, H. Fujita, E. Herrera-Viedma. A visual interaction consensus model for social network group decision making with trust propagation. Knowledge Based-Systems 122 (2017) 39-50. doi: 10.1016/j.knosys.2017.01.031
  
• [2118] M.A. Martínez, F.L. Rodríguez, M.J. Cobo, E. Herrera-Viedma. ¿Qué está pasando en el Área de Trabajo Social, según el Web of Science?. Cuadernos de Trabajo Social 30-1 (2017) 125-134. doi: 10.5209/CUTS.51495
  
• [2119] J. Castro, R. Yera, L. Martínez. An empirical study of natural noise management in group recommendation systems. Decision Support Systems 94 (2017) 1–11. doi: 10.1016/j.dss.2016.09.020
  
• [2135] A. Fernandez, S. Río, N.V. Chawla, F. Herrera. An insight into imbalanced Big Data classification: outcomes and challenges. Complex & Intelligent Systems 3:2 (2017) 105–120. doi: 10.1007/s40747-017-0037-9
  
• [2133] S. García, S. Ramírez-Gallego, J. Luengo, F. Herrera. Big Data: Preprocesamiento y calidad de datos. Novática (Revista de la Asociación de Técnicos de Informática), Monografía Big Data, 237 (2017) 17-23..
  Enlace a la revista completa
  
  
• [2137] O. Taylan, M.A. Zytoon, A. Morfeq, R. Al-Hmouz, E. Herrera-Viedma. Workplace assessment by fuzzy decision tree and TOPSIS methodologies to manage the occupational safety and health performance in food industries. J. of Intelligent and Fuzzy Systems, 33 (2017) 1209–1224.
  
• [2143] A. Fernandez, C.J. Carmona, M.J. del Jesus, F. Herrera. A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets. International Journal of Neural Systems 27 (2017) 1750028-1:1750028-21. doi: 10.1142/S0129065717500289
  
• [2145] Y. Xu, F.J. Cabrerizo, E. Herrera-Viedma. A consensus model for hesitant fuzzy preference relations and its application in water allocation management. Applied Soft Computing 58 (2017) 265-284. doi: 10.1016/j.asoc.2017.04.068
  
• [2146] T. Sabbah, A. Selamat, F.S. Al-Anzi, E. Herrera-Viedma, O. Krejcar. Modified frequency-based term weighting schemes for text classificationent. Applied Soft Computing, Vol. 58, 2017, Pages 193-206..
  
• [2147] L. Alcaide Muñoz, M.P. Rodríguez Bolivar, M.J. Cobo, E. Herrera-Viedma. Analysing the scientific evolution of e-government using a science mapping approach. Government Information Quarterly 34:3 (2017) 545-555. doi: 10.1016/j.giq.2017.05.002
  
• [2149] M. De la Flor-Martínez, P. Galindo-Moreno, E. Sánchez-Fernández, E. Adabal, M.J. Cobo, E. Herrera-Viedma. Evaluation of scientific output in Dentistry in Spanish universities. Medicina Oral Patología Oral y Cirugía Bucal, 22:4 (2017), e491-9. doi: doi:10.4317/medoral.21656
  
• [2150] Z-L. Zhang, X-G. Luo, S. García, F. Herrera. Cost-Sensitive back-propagation neural networks with binarization techniques in addressing multi-class problems and non-competent classifiers. Applied Soft Computing 56 (2017) 357-367. doi: 10.1016/j.asoc.2017.03.016
  
• [2151] D. Peralta, I. Triguero, S. García, Y. Saeys, J.M. Benítez, F. Herrera. Distributed incremental fingerprint identification with reduced database penetration rate using a hierarchical classification based on feature fusion and selection. Knowledge-Based Systems 126 (2017) 91-103. doi: 10.1016/j.knosys.2017.03.014
  
• [2153] S. Ramírez-Gallego, B. Krawczyk, S. García, M. Wozniak, F. Herrera. A survey on data preprocessing for data stream mining: Current status and future directions. Neurocomputing 239 (2017) 39-57. doi: 10.1016/j.neucom.2017.01.078
  
• [2154] D. Peralta, S. García, J.M. Benítez, F. Herrera. Minutiae-Based Fingerprint Matching Decomposition: Methodology for Big Data Frameworks. Information Sciences 408 (2017) 198-212. doi: 10.1016/j.ins.2017.05.001
  
• [2155] J.R. Cano, N.R. Aljohani, R.A. Abbasi, J.S. Alowidbi, S. García. Prototype selection to improve monotonic nearest neighbor. Engineering Applications of Artificial Intelligence 60 (2017) 128-135. doi: 10.1016/j.engappai.2017.02.006
  
• [2156] S. González, S. García, M. Lázaro, A.. Figueiras-Vidal, F. Herrera. Class Switching according to Nearest Enemy Distance for learning from highly imbalanced data-sets. Pattern Recognition 70 (2017) 12-24. doi: 10.1016/j.patcog.2017.04.028
  
• [2157] M.A. Jarwar, R.A. Abbasi, M. Mushtaq, O. Maqbool, N.R. Aljohani, A. Daud, J.S. Alowibdi, J.R. Cano, S. García, I. Chong. CommuniMents: A Framework for Detecting Community Based Sentiments for Events. International Journal on Semantic Web and Information Systems (IJSWIS) 13:2 (2017) 87-108. doi: 10.4018/IJSWIS.2017040106
  
• [2158] Z-L. Zhang, X-G. Luo, S. García, J-F. Tang, F. Herrera. Exploring the effectiveness of dynamic ensemble selection in the one-versus-one scheme. Knowledge-Based Systems 125 (2017) 53-63. doi: 10.1016/j.knosys.2017.03.026
  
• [2159] A. Rosales-Perez, S. García, J.A. Gonzalez, C.A.C. Coello, F. Herrera. An Evolutionary Multi-Objective Model and Instance Selection for Support Vector Machines with Pareto-based Ensembles. IEEE Transactions on Evolutionary Computation (Volume: 21, Issue: 6, Dec. 2017) 863-877. doi: 10.1109/TEVC.2017.2688863
  
• [2160] D. García-Gil, S. Ramírez-Gallego, S. García, F. Herrera. A comparison on scalability for batch big data processing on Apache Spark and Apache Flink. Big Data Analytics 2:1 (2017) 1. doi: 10.1186/s41044-016-0020-2
  
• [2170] S. Ramírez-Gallego, B. Krawczyk, S. García, M. Wozniak, J.M. Benítez, F. Herrera. Nearest Neighbor Classification for High-Speed Big Data Streams Using Spark. IEEE Transactions on Systems, Man, and Cybernetics: Systems 47:10 (2017) 2727-2739. doi: 10.1109/TSMC.2017.2700889
  
• [2180] J. García, H.M. Fardoun, D.M. Alghazzawi, J.R. Cano, S. García. MoNGEL: monotonic nested generalized exemplar learning. Pattern Analysis and Applications 20:2 (2017) 441–452. doi: 10.1007/s10044-015-0506-y
  
• [2190] S. Tabik, D. Peralta, A. Herrera-Poyatos, F. Herrera. A snapshot of image pre-processing for convolutional neural networks: case study of MNIST. International Journal of Computational Intelligence Systems 10 (2017) 555-568.
  
• [2196] J. Purswani, R. Romero Zaliz, A. Matin Platero, I. Guisado Requena, J. Gonzalez Lopez, C. Pozo. BSocial: Deciphering Social Behaviours within Mixed Microbial Populations. Frontiers in Microbiology 8:919 (2017). doi: 10.3389/fmicb.2017.00919
  
• [2197] J.F. Reinoso Gordo, M.J. Ibañez, R. Romero Zaliz. Parallelizing drainage network algorithm using free software: Octave as a solution. Mathematics and Computers in Simulation, Volumen 137, pp. 424-430, 2017. doi: 10.1016/j.matcom.2016.09.004
  
• [2203] M. Chica, J. Barranquero, T. Kajdanowicz, S. Damas, O. Cordón. Multimodal optimization: an effective framework for model calibration. Information Sciences 375:1 (2017) 79-97. doi: 10.1016/j.ins.2016.09.048
  
• [2204] I. Moya, M. Chica, J.L. Sáez-Lozano, O. Cordón. An agent-based model for understanding the influence of the 11-M terrorist attacks on the 2004 Spanish elections. Knowledge-based Systems 123 (2017) 200-216. doi: 10.1016/j.knosys.2017.02.015
  
• [2205] M. Chica, W. Rand. Agent-based decision support systems for managing word-of-mouth programs. Application to freemium business model. Journal of Marketing Research 54:5 (2017) 752-767. doi: 10.1509/jmr.15.0443
  
• [2213] C. Campomanes-Álvarez, B.R. Campomanes-Álvarez, O. Ibáñez, O. Cordón, S. Guadarrama. An experimental study on fuzzy distances for skull-face overlay in craniofacial superimposition. Fuzzy Sets and Systems 318 (2017) 100–119. doi: 10.1016/j.fss.2016.06.015
  
• [2248] O. Gómez, O. Ibáñez, O. Cordón. Improved image registration in skull–face overlay using expert knowledge. Journal: Progress in Artificial Intelligence 6:4 (2017) 285–298. doi: 10.1007/s13748-017-0124-6
  
• [2274] C. del Val, Bondar AN. Charged groups at binding interfaces of the PsbO subunit of photosystem II: A combined bioinformatics and simulation study. Journal: Biochimica et Biophysica Acta (BBA) - Bioenergetics. 2017 Jun;1858(6):432-441. doi: 10.1016/j.bbabio.2017.03.004
  
• [2312] G.P. Figueredo, I. Triguero, M. Mesgaspour, A.M. Guerra, J.M. Garibaldi, R. I. John. Detecting danger in roads: an immune-inspired technique to identify heavy goods vehicles incident hot spots. IEEE Transactions on Emerging Topics in Computational Intelligence, 1 (4) (2017), 248-258. doi: 10.1109/TETCI.2017.2721960
  
• [2316] J.A. Morente-Molinera, G. Kou, R. González-Crespo, J.M. Corchado, E. Herrera-Viedma. Solving multi-criteria group decision making problems under environments with a high number of alternatives using fuzzy ontologies and multi-granular linguistic modelling methods. Knowledge-Based Systems 137 (2017) 54-64.
  
• [2317] A. Yazidi, E. Herrera-Viedma. A new methodology for identifying unreliable sensors in data fusion. Knowledge-Based Systems, 136 ( 2017) 85-96.
  
• [2318] E. Herrera-Viedma, F.J. Cabrerizo, F. Chiclana, J. Wu, M.J. Cobo, K. Samuylov. Consensus in Group Decision Making and Social Networks. Studies in Informatics and Control 26:3 (2017) 259-268. doi: 10.24846/v26i3y201701
  
• [2323] A. Fernandez, A. Altalhi, S. Alshomrani, F. Herrera. Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications?. International Journal of Computational Intelligence Systems 10 (2017) 1211-1225. doi: 10.2991/ijcis.10.1.80
  
• [2322] I. Triguero, S. González, J.M. Moyano, S. García, J. Alcalá-Fdez, J. Luengo, A. Fernández, M.J. del Jesús, L. Sánchez and F. Herrera. KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining. International Journal of Computational Intelligence Systems 10 (2017) 1238-1249.
  
• [2334] C. Porcel, A. Ching-Lopez, J. Bernabé-Moreno, A. Tejeda-Lorente, E. Herrera-Viedma. Fuzzy linguistic recommender systems for the selective diffusion of information in digital libraries. Journal of Information Processing Systems, 13:4, (2017), 653-667. doi: 10.3745/JIPS.04.0035
  
• [2346] S Aldana, P García-Fernández, Alberto Rodríguez-Fernández, R. Romero-Zaliz, MB González, F Jiménez-Molinos, F Campabadal, F Gómez-Campos, JB Roldán. A 3D kinetic Monte Carlo simulation study of resistive switching processes in Ni/HfO2/Si-n+-based RRAMs. Journal of Physics D: Applied Physics 50:33 (2017) 335103. doi: 10.1088/1361-6463/aa7939
  
• [2355] C. García-Martínez, P.D. Gutiérrez, D. Molina, M. Lozano, F. Herrera. Since CEC 2005 competition on realparameter optimisation: a decade of research, progress and comparative analysis's weakness. Soft Computing, 21:19 (2017) 5573-5583. doi: 10.1007/s00500-016-2471-9
  
• [2356] A. Alonso-Betanzos, J.A. Gámez, F. Herrera, J.M. Puerta, J.C. Riquelme. Volume, variety and velocity in Data Science. Knowledge-Based Systems 117 (2017) 1-2. doi: 10.1016/j.knosys.2016.11.005
  
• [2357] J.A. Gámez, F. Herrera, J.M. Puerta. Guest Editorial: Recent Trends in Intelligent Systems. International Journal of Intelligent Systems 32 (2) (2017) 107-108. doi: 10.1002/int.21831
  
• [2358] X. Gou, H. Liao, Z. Xu, F. Herrera. Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: A case of study to evaluate the implementation status of haze controlling measures. Information Fusion 38 (2017) 22-34. doi: 10.1016/j.inffus.2017.02.008
  
• [2359] H. Liao, L. Jiang, Z. Xu, J. Xu, F. Herrera. A linear programming method for multiple criteria decision making with probabilistic linguistic information. Information Sciences 415 (2017) 341-355. doi: 10.1016/j.ins.2017.06.035
  
• [2360] Y. Dong, Z. Ding, L. Martínez, F. Herrera. Managing consensus based on leadership in opinion dynamics. Information Sciences 398 (2017) 187–205. doi: 10.1016/j.ins.2017.02.052
  
• [2366] A. Valdivia, M.V. Luzón, F. Herrera. Sentiment Analysis in TripAdvisor. IEEE Intelligent Systems 32:4 (2017) 72-77. doi: 10.1109/MIS.2017.3121555
  
• [2368] J. R. Cano, S. García. Training Set Selection for Monotonic Ordinal Classification. Data & Knowledge Engineering 112 (2017) 94-105. doi: 10.1016/j.datak.2017.10.003
  
• [2369] F. J. Estrella, S. Cevik Onar, R.M. Rodríguez, B. Oztaysi, L. Martínez, C. Kahraman. Selecting firms in University technoparks: A hesitant linguistic fuzzy TOPSIS model for heterogeneous contexts. Journal of Intelligent and Fuzzy Systems 33:2 (2017) 1155-1172. doi: 10.3233/JIFS-16727
  
• [2370] Y. Zulueta, R.M. Rodríguez, R. Bello, L. Martinez. A Hesitant Heterogeneous Approach for Environmental Impact Significance Assessment. Journal of Environmental Informatics 29:2 (2017) 74-87. doi: 10.3808/jei.201700363
  
• [2375] de Erausquin G, Molina J, Balda M, Kamis D, Calvó M, Padilla E, Guerrero G, Bourdieu M, Molina Rangeon M, Gonzalez Aleman G, Strejilevich S, Florenzano N, Conesa H, Escobar J, Zwir I, and Cloninger CR. Parkinsonian motor impairment predicts personality domains related to genetic risk and treatment outcomes. Journal: NPJ Schizophr. 2017; 3: 16036. doi: 10.1038/npjschz.2016.36
  
• [2377] E. Bermejo, C. Campomanes-Alvarez, A. Valsecchi, O. Ibáñez, S. Damas, O. Cordón. Genetic algorithms for skull-face overlay including mandible articulation. Information Sciences 420 (2017) 200-217. doi: 10.1016/j.ins.2017.08.029
  
• [2400] P. Morales, J. Luengo, L.P.F. Garcia, A.C. Lorena, A.C.P.L.F. de Carvalho and F. Herrera. The NoiseFiltersR Package: Label Noise Preprocessing in R. The R Journal 9:1 (2017) 219-228.
  
• [2418] D. Bérard, B. Sicardy, J. I. B. Camargo, J. Desmars, F. Braga-Ribas, J.-L. Ortiz, R. Duffard, N. Morales, E. Meza, R. Leiva, G. Benedetti-Rossi, R. Vieira-Martins, A.-R. Gomes Júnior, M. Assafin, F. Colas, J.-L. Dauvergne, P. Kervella, J. Lecacheux, L. Maquet, F. Vachier, S. Renner, B. Monard, A. A. Sickafoose, H. Breytenbach, A. Genade, W. Beisker, K.-L. Bath, H.-J. Bode, M. Backes, V. D. Ivanov, E. Jehin, M. Gillon, J. Manfroid, J. Pollock, G. Tancredi, S. Roland, R. Salvo, L. Vanzi, D. Herald, D. Gault, S. Kerr, H. Pavlov, K. M. Hill, J. Bradshaw, M. A. Barry, A. Cool, B. Lade, A. Cole, J. Broughton, J. Newman, R. Horvat, D. Maybour, D. Giles, L. Davis, R. A. Paton, B. Loader, A. Pennell, P.-D. Jaquiery, S. Brillant, F. Selman, C. Dumas, C. Herrera, G. Carraro, L. Monaco, A. Maury, A. Peyrot, J.-P. Teng-Chuen-Yu, A. Richichi, P. Irawati, C. De Witt, P. Schoenau, R. Prager, C. Colazo, R. Melia, J. Spagnotto, A. Blain, S. Alonso, A. Román, P. Santos-Sanz, J.-L. Rizos, J.-L. Maestre, D. Dunham. The Structure of Chariklo’s Rings from Stellar Occultations. The Astronomical Journal 154(4):144. doi: 10.3847/1538-3881/aa830d
  
• [2426] M. Victor, M. Mondragon, V. Garcia-Diaz, R. González-Crespo, C. Porcel, E. Herrera-Viedma. Adaptive contents for Interactive TV guided by machine learning based on predictive sentiment analysis of data. Soft Computing, 1-22. doi: https://doi.org/10.1007/s00500-017-2530-x
  

2016 (75)

• [1925] José A. Sáez, J. Luengo, F. Herrera. Evaluating the classifier behavior with noisy data considering performance and robustness: The Equalized Loss of Accuracy measure. Neurocomputing 176 (2016) 26-35. doi: 10.1016/j.neucom.2014.11.086
  
• [1924] José A. Sáez, M. Galar, J. Luengo, F. Herrera. INFFC: An iterative class noise filter based on the fusion of classifiers with noise sensitivity control. Information Fusion 27 (2016) 505-636. doi: 10.1016/j.inffus.2015.04.002
  
• [1849] A. Palacios, L. Sanchez, I. Couso. An extension of the FURIA classification algorithm to low quality data through fuzzy rankings and its application to the early diagnosis of dyslexia. Neurocomputing 176 (2016) 60-71.
  
• [2106] Y. Dong, C-C. Li, F. Chiclana, E. Herrera-Viedma. Average-case consistency measurement and analysis of interval-valued reciprocal preference relations. Knowledge-Based Systems 114C (2016) pp. 108-117.
  
• [1896] S. Ramírez-Gallego, S. García, J.M. Benítez, F. Herrera. Multivariate Discretization Based on Evolutionary Cut Points Selection for Classification. IEEE Transaction on Cybernetics 46:3 (2016) 595-608. doi: 10.1109/TCYB.2015.2410143
  
• [1899] J.A. Morente-Molinera, R. Al-hmouz, A. Morfeq, A.S. Balamash, E. Herrera-Viedma. A Decision Support System for Decision Making in Changeable and Multi-Granular Fuzzy Linguistic Contexts. J. of Mult.-Valued Logic & Soft Computing 26.3-5 (2016) 485-514.
  
• [1920] J. Alcalá-Fdez, J.M. Alonso. A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends and Prospects. IEEE Transactions on Fuzzy Systems 24:1 (2016) 40-56. doi: 10.1109/TFUZZ.2015.2426212
  COMPLEMENTARY MATERIAL to the paper: software, bibliography, events, etc
  
  
• [2079] D. Martin, J. Alcalá-Fdez, A. Rosete, F. Herrera. NICGAR: a Niching Genetic Algorithm to Mine a Diverse Set of Interesting Quantitative Association Rules. Information Sciences 355-356 (2016) 208-228. doi: 10.1016/j.ins.2016.03.039
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• [1949] M. González, C. Bergmeir, I. Triguero, Y. Rodríguez, J.M. Benítez. On the Stopping Criteria for k-Nearest Neighbor in Positive Unlabeled Time Series Classification Problems. Information Sciences 328 (2016) 42-59. doi: 10.1016/j.ins.2015.07.061
  
• [1954] J.A. Morente-Molinera, R. Wikström, E. Herrera-Viedma, C. Carlsson. An implementation of a linguistic mobile decision support system based on fuzzy ontologies to facilitate knowledge mobilization. Decision Support Systems 81 (2016) 66-75. doi: 10.1016/j.dss.2015.09.001
  
• [1961] J.A. Morente-Molinera, I.J. Pérez, M.R. Ureña, E. Herrera-Viedma. Creating knowledge databases for storing and sharing people knowledge automatically using group decision making and fuzzy ontologies. Information Sciences 328 (2016) 418-434. doi: 10.1016/j.ins.2015.08.051
  
• [1962] J.A. Moral-Muñoz, M.J. Cobo, F. Chiclana, A. Collop, E. Herrera-Viedma. Analyzing highly cited papers in Intelligent Transportation Systems. IEEE Transactions on Intelligent Transportation Systems 17:4 (2016) 993 - 1001. doi: 10.1109/TITS.2015.2494533
  
• [1964] J. Derrac, F. Chiclana, S. García, F. Herrera. Evolutionary fuzzy k-nearest neighbors algorithm using interval-valued fuzzy sets. Information Sciences 329 (2016) 144-163. doi: 10.1016/j.ins.2015.09.007
  
• [1965] Y. Xu, F. Herrera, H. Wang. A distance-based framework to deal with ordinal and additive inconsistencies for fuzzy reciprocal preference relations. Information Sciences 380:20 (2016) 189-205. doi: 10.1016/j.ins.2015.08.034
  
• [1966] J. Mendel, H. Hagras, H. Bustince Sola, F. Herrera. Comments on “Interval type-2 fuzzy sets are generalization of interval-valued fuzzy sets: towards a wide view on their relationship”[2]. IEEE Transactions on Fuzzy Systems 24:1 (2016) 249-250. doi: 10.1109/TFUZZ.2015.2446508
  
• [1968] N. Verbiest, J. Derrac, C. Cornelis, S. García, F. Herrera. Evolutionary Wrapper Approaches for Training Set Selection as Preprocessing Mechanism for Support Vector Machines: Experimental Evaluation and Support Vector Analysis. Applied Soft Computing 38 (2016) 10-22. doi: 10.1016/j.asoc.2015.09.006
  
• [1975] R. Yera, J. Castro, L. Martínez. A fuzzy model for managing natural noise in recommender systems. Applied Soft Computing 40 (2016) 187-198. doi: 10.1016/j.asoc.2015.10.060
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• [1985] M. de la Flor, P. Galindo-Moreno, E. Sánchez-Fernandez, A. Piatteli, M.J. Cobo, E. Herrera-Viedma. H-classic: A new method to identify classic articles in implant dentistry, periodontics, and oral surgery. Clinical Oral Implants Research 27:10 (2016), 1317–1330. doi: 10.1111/clr.12749
  
• [1986] R. Heradio, H. Perez-Morago, D. Fernandez-Amoros, F.J. Cabrerizo, E. Herrera-Viedma. A Bibliometric Analysis of 20 Years of Research on Software Product Lines. Information and Software Technology 72 (2016) 1-15. doi: 10.1016/j.infsof.2015.11.004
  
• [2070] A. Fernandez, M. Elkano, M. Galar, J.A. Sanz, S. Alshomrani, H. Bustince, F. Herrera. Enhancing Evolutionary Fuzzy Systems for Multi-Class Problems: Distance-based Relative Competence Weighting with Truncated Confidences (DRCW-TC). International Journal of Approximate Reasoning 73 (2016) 108-122. doi: 10.1016/j.ijar.2016.02.005
  
• [1996] S. Ramírez-Gallego, S. García, H. Mouriño Talín, D. Martínez-Rego, V. Bolón-Canedo, A. Alonso-Betanzos, J. M. Benítez, F. Herrera. Data discretization: taxonomy and big data challenge. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 6:1 (2016) 5-21. doi: 10.1002/widm.1173
  
• [1998] Y. Dong, H. Zhang, E. Herrera-Viedma. Integrating experts' weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors. Decision Support Systems 84(2016) 1-15.
  
• [2004] M. Chica, J. Bautista, O. Cordón, S. Damas. A multiobjective model and evolutionary algorithms for robust time and space assembly line balancing under uncertain demand. Omega 54:1 (2016) 55-68. doi: 10.1016/j.omega.2015.04.003
  
• [2005] A. Sancho-Asensio, A. Orriols-Puig, J. Casillas. Evolving association streams. Information Sciences 334-335 (2016) 250-272. doi: 10.1016/j.ins.2015.11.043
  
• [2101] S. Vluymans, I. Triguero, C. Cornelis, Y. Saeys. EPRENNID: An Evolutionary Prototype Reduction Based Ensemble for Nearest Neighbor Classification of Imbalanced Data. Neurocomputing 216 (2016) 596-610. doi: 10.1016/j.neucom.2016.08.026
  
• [2009] E. Ramentol, I. Gondres, S. Lajes, R. Bello, Y. Caballero, C. Cornelis, F. Herrera. Fuzzy-rough imbalanced learning for the diagnosis of High Voltage Circuit Breaker maintenance: The SMOTE-FRST-2T algorithm. Engineering Applications of Artificial Intelligence 48 (2016) 134-139. doi: 10.1016/j.engappai.2015.10.009
  
• [2097] M. Lozano, M. Laguna, R. Martí, F. J. Rodriguez, C. García-Martínez. A genetic algorithm for the minimum generating set problem. Applied Soft Computing 48 (2016) 254-264. doi: 10.1016/j.asoc.2016.07.020
  
• [2011] B. Krawczyk, M. Galar, L. Jelén, F. Herrera. Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy. Applied Soft Computing 38 (2016) 714-726. doi: 10.1016/j.asoc.2015.08.060
  
• [2013] S. Vluymans, D. Sanchez-Tarrago, Y. Saeys, C. Cornelis, F. Herrera. Fuzzy Multi-Instance Classifiers. IEEE Transactions on Fuzzy Systems 24:6 (2016) 1395-1409. doi: 10.1109/TFUZZ.2016.2516582
  
• [2014] S. García, J. Luengo, F. Herrera. Tutorial on practical tips of the most influential data preprocessing algorithms in data mining. Knowledge-Based Systems 98 (2016) 1–29. doi: 10.1016/j.knosys.2015.12.006
  COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes
  
  
• [2015] R.M. Rodríguez, B. Bedregal, H. Bustince, Y.C. Dong, B. Farhadinia, C. Kahraman, L. Martínez, V. Torra, Y.J. Xu, Z.S. Xu, F. Herrera. A position and perspective analysis of hesitant fuzzy sets on information fusion in decision making. Towards high quality progress. Information Fusion 29 (2016) 89-97. doi: 10.1016/j.inffus.2015.11.004
  
• [2016] S. Vluymans, D. Sánchez-Tarragó, Y. Saeys, C. Cornelis, F. Herrera. Fuzzy rough classifiers for class imbalanced multi-instance data. Pattern Recognition 53 (2016) 36-45. doi: 10.1016/j.patcog.2015.12.002
  
• [2017] H. Bustince, E. Barrenechea, M. Pagola, J. Fernandez, Z. Xu, B. Bedregal, J. Montero, H. Hagras, F. Herrera, B. De-Baets. A historical account of types of fuzzy sets and their relationships. IEEE Transactions on Fuzzy Systems 24:1 (2016) 179-194. doi: 10.1109/TFUZZ.2015.2451692
  
• [2018] N. Bova, V. Gál, O. Ibáñez, O. Cordón. Deformable models direct supervised guidance: A novel paradigm for automatic image segmentation. Neurocomputing 177 (2016) 317–333. doi: 10.1016/j.neucom.2015.11.023
  
• [2020] C. Campomanes-Álvarez, O. Ibáñez, O. Cordón. Design of criteria to assess craniofacial correspondence in forensic identification based on computer vision and fuzzy integrals. Applied Soft Computing 46 (2016) 596-612. doi: 10.1016/j.asoc.2015.11.006
  
• [2052] L.G. Perez, F. Mata, F. Chiclana, G. Kou, E. Herrera-Viedma. Modelling influence in group decision making. Soft Computing 20:4 (2016) 1653-1665. doi: 10.1007/s00500-015-2002-0
  
• [2071] M. Lozano, F. J. Rodriguez, D. Peralta, C. García-Martínez. Randomized Greedy Multi-Start Algorithm for the Minimum Common Integer Partition Problem. Engineering Applications of Artificial Intelligence 50 (2016) 226-235. doi: 10.1016/j.engappai.2016.01.037
  
• [2072] I. Triguero, C. Vens. Labelling Strategies for Hierarchical Multi-Label Classification Techniques. Pattern Recognition 56 (2016) 170-183. doi: 10.1016/j.patcog.2016.02.017
  
• [2073] M. Galar, A. Fernandez, E. Barrenechea, H. Bustince, F. Herrera. Ordering-Based Pruning for Improving the Performance of Ensembles of Classifiers in the Framework of Imbalanced Datasets. Information Sciences 354 (2016) 178-196. doi: 10.1016/j.ins.2016.02.056
  
• [2074] M.R. Ureña, F.J. Cabrerizo, J.A. Morente-Molinera, E. Herrera-Viedma. GDM-R: A new framework in R to support fuzzy group decision making processes. Information Sciences 357 (2016) 161-181. doi: 10.1016/j.ins.2016.03.008
  
• [2075] D. Peralta, I. Triguero, S. García, F. Herrera, J.M. Benítez. DPD-DFF: A Dual Phase Distributed Scheme with Double Fingerprint Fusion for Fast and Accurate Identification in Large Databases. Information Fusion 32 (2016) 40–51. doi: 10.1016/j.inffus.2016.03.002
  
• [2076] A. Cid-López, M. J. Hornos, R. A. Carrasco-González, E. Herrera-Viedma. Applying a Linguistic Multi-Criteria Decision-Making Model to the Analysis of ICT Suppliers' Offers. Expert Systems with Applications 57 (2016) 127–138. doi: 10.1016/j.eswa.2016.03.025
  
• [2077] R. Heradio, L. de la Torre, D. Galan, F.J. Cabrerizo, E. Herrera-Viedma, S. Dormido. Virtual and Remote Labs in Education: a Bibliometric Analysis. Computers & Education 98 (2016) 14–38. doi: 10.1016/j.compedu.2016.03.010
  
• [2078] C. De Maio, G. Fenza, V. Loia, F. Orciuoli, E. Herrera-Viedma. A Framework for Context-aware Heterogeneous Group Decision Making in Business Processes. Knowledge-Based Systems 102 (2016) 39–50.
  
• [2080] S. Massanet, J. V. Riera, J.Torrens, E. Herrera-Viedma. A model based on subjective linguistic preference relations for group decision making problems. Information Sciences 2016) 355–356, 249–264.
  
• [2081] P. Mesejo, O. Ibáñez, O. Cordón, S. Cagnoni. A Survey on Image Segmentation using Metaheuristic-based Deformable Models: State of the Art and Critical Analysis. Applied Soft Computing 44 (2016) 1-29. doi: 10.1016/j.asoc.2016.03.004
  
• [2082] A. Fernandez, C.J. Carmona, M.J. del Jesus, F. Herrera. A View on Fuzzy Systems for Big Data: Progress and Opportunities. International Journal of Computational Intelligence Systems, 9:1 (2016), 69-80. doi: 10.1080/18756891.2016.1180820
  
• [2087] Y. Dong, H. Zhang, E. Herrera-Viedma. Consensus reaching model in the complex and dynamic MAGDM problem. Knowledge-Based Systems 106 (2016) 206–219. doi: 10.1016/j.knosys.2016.05.046
  
• [2090] C. Figueroa, H. Ordóñez, J. C. Corrales, C. Cobos, L. K. Wives, E. Herrera-Viedma. Improving Business Process Retrieval Using Categorization and Multimodal Search. Knowledge-Based Systems 110 (2016) 49-59. doi: 10.1016/j.knosys.2016.07.014
  
• [2103] J. Luengo, A. M. García-Vico, M. D. Pérez-Godoy, C. J. Carmona. The influence of noise on the evolutionary fuzzy systems for subgroup discovery. Soft Computing 20:11 (2016) 4313-4330. doi: 10.1007/s00500-016-2300-1
  
• [2109] B. Lacroix, D. Molina, F. Herrera. Region-based memetic algorithm with archive for multimodal optimisation. Information Sciences 367-368 (2016) 719-746. doi: 10.1016/j.ins.2016.05.049
  
• [2161] S. Gutiérrez, S. García. Landmark-based music recognition system optimisation using genetic algorithms. Multimedia Tools and Applications 75:24 (2016) 16905-16922. doi: 10.1007/s11042-015-2963-0
  
• [2162] S. García, S. Ramírez-Gallego, J. Luengo, J.M. Benítez, F. Herrera. Big data preprocessing: methods and prospects. Big Data Analytics 1:9 (2016). doi: 10.1186/s41044-016-0014-0
  
• [2164] Z-L. Zhang, B. Krawczyk, S. García, A. Rosales-Pérez, F. Herrera. Empowering one-vs-one decomposition with ensemble learning for multi-class imbalanced data. Knowledge-Based Systems 106 (2016) 251-263. doi: 10.1016/j.knosys.2016.05.048
  
• [2165] P.A. Gutiérrez, S. García. Current prospects on ordinal and monotonic classification. Progress in Artificial Intelligence 5:3 (2016), 171-179. doi: 10.1007/s13748-016-0088-y
  
• [2176] J. García, A.M. AlBar, N.R. Aljohani, J.R. Cano, S. García. Hyperrectangles selection for monotonic classification by using evolutionary algorithms. International Journal of Computational Intelligence Systems 9:1 (2016), 184-201. doi: 10.1080/18756891.2016.1146536
  
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• [2186] R. Romero Zaliz, J.F. Reinoso Gordo, D. Barrera Rosillo, F.J. Ariza Lopez. Minimizing B-spline knots in representative road axis from GPS points cloud. Mathematical Methods in the Applied Sciences, Volume 39, Issue 16, 15 November 2016, Pages 4773–4779.. doi: 10.1002/mma.3772
  
• [2195] J.F. Reinoso Gordo, F.J. Ariza Lopez, D. Barrera Rosillo, A. Gomez Blanco, R. Romero Zaliz. A fitted B-spline method to derive a representative 3D axis from a set of multiple road traces. Geocarto International, Volumen 31, Numero 8, pp. 1-13, 2016. doi: 10.1080/10106049.2015.1086902
  
• [2201] C. Zarco, S. del Barrio-García, O. Cordón. Propuesta de Rankings de Universidades Españolas en Redes Sociales. El Profesional de la Información 25:4 (2016) 684-698.
  
• [2202] M. Chica, O. Cordón, S. Damas, V. Iglesias, J. Mingot. Identimod: Modeling and Managing Brand Value using Soft Computing. Decision Support Systems 89 (2016) 41–55. doi: 10.1016/j.dss.2016.06.007
  
• [2211] O. Ibáñez, R. Vicente, D. Navega, B. R. Campomanes-Álvarez, C. Cattaneo, R. Jankauskas, M. I. Huete, F. Navarro, R. Hardiman, E. Ruiz, K. Imaizumi, F. Cavalli, E. Veselovskaya, +5 authors, S. Damas. MEPROCS framework for Craniofacial Superimposition: validation study. Legal Medicine 23 (2016) 99-108. doi: 10.1016/j.legalmed.2016.10.007
  
• [2212] O. Ibáñez, A. Valsecchi, F. Cavalli, M.I. Huete, B.R. Campomanes-Álvarez, C. Campomanes-Álvarez, R. Vicente, D.S. Navega, A. Ross, C. Wilkinson, R. Jankauskas, K. Imaizumi, +15 authors, S. Damas. Study on the criteria for assessing skull-face correspondence in craniofacial superimposition. Legal Medicine 23 (2016) 59-70. doi: 10.1016/j.legalmed.2016.09.009
  
• [2252] P.D. Gutiérrez, M. Lastra, J. Bacardit, J.M. Benítez, F. Herrera. GPU-SME-kNN: Scalable and memory efficient kNN and lazy learning using GPUs. Information Sciences 373, 165-182. doi: 10.1016/j.ins.2016.08.089
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• [2258] R.M. Rodríguez, Á. Labella, L. Martínez. An Overview on Fuzzy Modelling of Complex Linguistic Preferences in Decision Making. International Journal of Computational Intelligence Systems 9 (2016) 81-94. doi: 10.1080/18756891.2016.1180821
  
• [2260] C. Wei, F. Yan, R.M. Rodríguez. Entropy measures for hesitant fuzzy sets and their application in multi-criteria decision-making. Journal of Intelligent & Fuzzy Systems 31 (2016) 673-685. doi: 10.3233/IFS-2180
  
• [2261] X. Yejun, L. Chen, R.M. Rodríguez, F. Herrera, H. Wang. Deriving the priority weights from incomplete hesitant fuzzy preference relations in group decision making. Knowledge-Based Systems 99 (2016) 71-78. doi: 0950-7051
  
• [2340] H. Velarde, C. Santiesteban, A. Garcia, J. Casillas. Analyzing the effect of variables in the software development effort estimation. IEEE Latin America Transactions 14:8 (2016) 3797-3803. doi: 10.1109/TLA.2016.7786366
  
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• [2373] E. Monasterio, O. Mei-Dan, A.C. Hackney, A.R. Lane, I. Zwir, S. Rozsa , C.R. Cloninger. Stress reactivity and personality in extreme sport athletes: The psychobiology of BASE jumpers.. Journal: Physiol Behav. 2016 Sep 29;167:289-297. doi: 10.1016/j.physbeh.2016.09.025
  
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2015 (88)

• [1699] J. Luengo, F. Herrera. An automatic extraction method of the domains of competence for learning classifiers using data complexity measures. Knowledge and Information Systems 42:1 (2015) 147-180. doi: 10.1007/s10115-013-0700-4
  
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  COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes
  
  
• [1730] M.A. Martínez-Sánchez, M.J. Cobo, M. Herrera, E. Herrera-Viedma. Analyzing the Scientific Evolution of Social Work Discipline Using Science Mapping. Research on Social Work Practice 5:2 (2015) 257-277. doi: 10.1177/1049731514522101
  
• [1734] V. López, S. Río, J.M. Benítez, F. Herrera. Cost-Sensitive Linguistic Fuzzy Rule Based Classification Systems under the MapReduce Framework for Imbalanced Big Data. Fuzzy Sets and Systems 258 (2015) 5-38. doi: 10.1016/j.fss.2014.01.015
  
• [1769] I. Triguero, D. Peralta, J. Bacardit, S. García, F. Herrera. MRPR: A MapReduce Solution for Prototype Reduction in Big Data Classification. Neurocomputing 150 (2015), 331-345. doi: 10.1016/j.neucom.2014.04.078
  
• [1784] P. Mesejo, A. Valsecchi, L. Marrakchi-Kacem, S. Cagnoni, S. Damas. Biomedical image segmentation using geometric deformable models and metaheuristics. Computerized Medical Imaging and Graphics 43 (2015) 167-178. doi: 10.1016/j.compmedimag.2013.12.005
  
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• [1788] I. Triguero, S. García, F. Herrera. SEG-SSC: A Framework based on Synthetic Examples Generation for Self-Labeled Semi-Supervised Classification. IEEE Transactions on Cybernetics 45:4 (2015) 622-634. doi: 10.1109/TCYB.2014.2332003
  
• [1790] F. Charte, A.J. Rivera, M.J. del Jesus, F. Herrera. Addressing imbalance in multilabel classification: Measures and random resampling algorithms. Neurocomputing 163 (2015) 3-16. doi: 10.1016/j.neucom.2014.08.091
  
• [1811] M. Galar, A. Fernandez, E. Barrenechea, F. Herrera. DRCW-OVO: Distance-based Relative Competence Weighting Combination for One-vs-One Strategy in Multi-class Problems. Pattern Recognition 48 (2015) 28-42. doi: 10.1016/j.patcog.2014.07.023
  
• [1813] S. Elhag, A. Fernandez, A. Bawakid, S. Alshomrani, F. Herrera. On the Combination of Genetic Fuzzy Systems and Pairwise Learning for Improving Detection Rates on Intrusion Detection Systems. Expert Systems with Applications 42:1 (2015) 193–202. doi: 10.1016/j.eswa.2014.08.002
  
• [1814] J.A. Sanz, D. Bernardo, F. Herrera, H. Bustince, H. Hagras. A Compact Evolutionary Interval-Valued Fuzzy Rule-Based Classification System for the Modeling and Prediction of Real-World Financial Applications with Imbalanced Data. IEEE Transactions on Fuzzy Systems 23:4 (2015) 973-990. doi: 10.1109/TFUZZ.2014.2336263
  
• [1815] Y. Dong, C.-C. Li, F. Herrera. An optimization-based approach to adjusting unbalanced linguistic preference relations to obtain a required consistency level. Information Sciences 292 (2015) 27-38. doi: 10.1016/j.ins.2014.08.059
  
• [1819] S. Alshomrani, A. Bawakid, S.-O. Shim, A. Fernandez, F. Herrera. A Proposal for Evolutionary Fuzzy Systems using Feature Weighting: Dealing with Overlapping in Imbalanced Datasets. Knowledge-Based Systems 73 (2015) 1-17. doi: 10.1016/j.knosys.2014.09.002
  
• [1820] E.M. Murgado-Armenteros, M. Gutiérrez-Salcedo, F.J. Torres-Ruiz, M.J. Cobo. Analysing the Conceptual Evolution of Qualitative Marketing Research through Science Mapping Analysis. Scientometrics 102:1 (2015) 519-557. doi: 10.1007/s11192-014-1443-z
  
• [1822] M. Lastra, D. Molina, J.M. Benítez. A high performance memetic algorithm for extremely high-dimensional problems. Information Sciences, 293 (2015) 35-58. doi: 10.1016/j.ins.2014.09.018
  
• [1823] Y. Dong, E. Herrera-Viedma. Consistency-driven automatic methodology to set interval numerical scales of 2-tuple linguistic term sets and its use in the linguistic GDM with preference relation. IEEE Transactions on Cybernetics, 45:4 (2015) 780-792.
  
• [1824] José A. Sáez, J. Luengo, Jerzy Stefanowski, F. Herrera. SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering. Information Sciences 291 (2015) 184-203. doi: 10.1016/j.ins.2014.08.051
  COMPLEMENTARY MATERIAL to the paper
  
  
• [1826] M. Chica, O. Cordón, S. Damas, J. Bautista. Interactive Preferences in Multiobjective Ant Colony Optimization for Assembly Line Balancing. Soft Computing 19:10 (2015) 2891-2903. doi: 10.1007/s00500-014-1451-1
  
• [1827] A. Rodriguez-Ledesma, M.J. Cobo, C. Lopez-Pujalte, E. Herrera-Viedma. An overview of Animal Science Research 1945-2011 through Science Mapping Analysis. Journal of Animal Breeding and Genetics 132:6 (2015) 475-497. doi: 10.1111/jbg.12124
  
• [1831] M.A. Martínez, M. Herrera, E. Contreras, A.A. Ruíz, E. Herrera-Viedma. Characterizing Highly Cited Papers in Social Work Through H-Classics. Scientometrics 102 (2015) 1713-1729. doi: 10.1007/s11192-014-1460-y
  
• [1832] A. Palacios, J.L. Palacios, L. Sánchez, J. Alcalá-Fdez. Genetic Learning of the Membership Functions for Mining Fuzzy Association Rules from Low Quality Data. Information Sciences 295 (2015) 358-378. doi: 10.1016/j.ins.2014.10.027
  
• [1834] H. Bustince, J. Fernandez, H. Hagras, F. Herrera. Interval Type-2 Fuzzy Sets are generalization of Interval-Valued Fuzzy Sets: Towards a Wider view on their relationship. IEEE Transactions on Fuzzy Systems 23:5 (2015) 1876-1882. doi: 10.1109/TFUZZ.2014.2362149
  
• [1843] M. Elkano, M. Galar, J.A. Sanz, A. Fernandez, E. Barrenechea, F. Herrera, H. Bustince. Enhancing multi-class classification in FARC-HD fuzzy classifier: On the synergy between n-dimensional overlap functions and decomposition strategies. IEEE Transactions on Fuzzy Systems 23:5 (2015) 1562-1580. doi: 10.1109/TFUZZ.2014.2370677
  
• [1845] Y. Dong, X. Chen, F. Herrera. Minimizing adjusted simple terms in the consensus reaching process with hesitant linguistic assessments in group decision making. Information Sciences 297 (2015) 95–117. doi: 10.1016/j.ins.2014.11.011
  
• [1846] E. Ramentol, S. Vluymans, N. Verbiest, Y. Caballero, R. Bello, C. Cornelis, F. Herrera. IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification. IEEE Transactions on Fuzzy Systems 23:5 (2015) 1622-1637. doi: 10.1109/TFUZZ.2014.2371472
  
• [1855] J.A. Morente-Molinera, I.J. Pérez, M.R. Ureña, E. Herrera-Viedma. On multi-granular fuzzy linguistic modelling in group decision making problems: a systematic review and future trends. Knowledge-Based Systems 74 (2015) 49-60. doi: 10.1016/j.knosys.2014.11.001
  
• [1856] Tianjun Liao, D. Molina, Thomas Stützle. Performance evaluation of automatically tuned continuous optimizers on different benchmark sets. Applied Soft Computing, 27 (2015) 490–503. doi: 10.1016/j.asoc.2014.11.006
  
• [1854] J. Bernabé-Moreno, A. Tejeda-Lorente, C. Porcel, E. Herrera-Viedma. A new model to quantify the impact of a topic in a location over time with Social Media. Expert Systems with Applications 7:1 (2015) 3381-3395. doi: 10.1016/j.eswa.2014.11.067
  
• [1857] J. Bernabé-Moreno, A. Tejeda-Lorente, C. Porcel, H.Fujita, E. Herrera-Viedma. CARESOME: A System to Enrich Marketing Customers Acquisition and Retention Campaigns Using Social Media. Knowledge-Based Systems 80 (2015) 163-179. doi: 10.1016/j.knosys.2014.12.033
  
• [1858] M.J. Cobo, M.A. Martínez, M. Gutiérrez-Salcedo, H. Fujita, E. Herrera-Viedma. 25 years at Knowledge-Based Systems: A bibliometric Analysis. Knowledge-Based Systems 80 (2015) 3-13. doi: 10.1016/j.knosys.2014.12.035
  
• [1859] M.R. Ureña, F. Chiclana, J.A. Morente-Molinera, E. Herrera-Viedma. Managing Incomplete Preference Relations in Decision Making: A Review and Future Trends. Information Sciences 302:1 (2015) 14-32. doi: 10.1016/j.ins.2014.12.061
  
• [1860] S. Río, V. López, J.M. Benítez, F. Herrera. A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules. International Journal of Computational Intelligence Systems 8:3 (2015) 422-437. doi: 10.1080/18756891.2015.1017377
  
• [1862] M. Lozano, F. J. Rodriguez, C. García-Martínez. A Two-Stage Constructive Method for the Unweighted Minimum String Cover Problem. Knowledge-Based Systems 77 (2015) 103-113. doi: 10.1016/j.knosys.2015.01.003
  
• [1863] A. Fernandez, V. López, M.J. del Jesus, F. Herrera. Revisiting Evolutionary Fuzzy Systems: Taxonomy, Applications, New Trends and Challenges. Knowlegde Based Systems 80 (2015) 109–121. doi: 10.1016/j.knosys.2015.01.013
  
• [1864] J.A. Moral-Muñoz, B. Esteban-Moreno, M. Arroyo-Morales, M.J. Cobo, E. Herrera-Viedma. Agreement between face-to-face and free software video analysis for assessing hamstring flexibility in adolescents. Journal of Strength and Conditioning Research 29:9 (2015) 2661-2665. doi: 10.1519/JSC.0000000000000896
  
• [1865] C. García-Martínez, C. Blum, F. J. Rodriguez, M. Lozano. The Firefighter Problem: Empirical Results on Random Graphs. Computers & Operations Research 60 (2015) 55-66. doi: http://dx.doi.org/10.1016/j.cor.2015.02.004
  
• [1866] P. Mesejo, O. Ibáñez, E. Fernández-Blanco, F. Cedrón, A. Pazos, A. B. Porto-Pazos. Artificial Neuron-Glia Networks Learning Approach Based On Cooperative Coevolution. International Journal of Neural Systems 25:4 (2015) 1550012. doi: 10.1142/S0129065715500124
  
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• [1888] J. Wu, F. Chiclana, E. Herrera-Viedma. Trust Based Consensus Model for Social Network in an Incomplete Linguistic Information Context. Applied Soft Computing 35 (2015) 827-839. doi: 10.1016/j.asoc.2015.02.023
  
• [1889] J. Serrano-Guerrero, J.A. Olivas, F.P. Romero, E. Herrera-Viedma. Sentiment Analysis: A Review and Comparative Analysis of Web Service. Information Science 311 (2015) 18-38. doi: 10.1016/j.ins.2015.03.040
  
• [1890] M. Galar, J. Derrac, D. Peralta, I. Triguero, D. Paternain, C. Lopez-Molina, S. García, J.M. Benítez, M. Pagola, E. Barrenechea, H. Bustince, F. Herrera. A Survey of Fingerprint Classification Part I: Taxonomies on Feature Extraction Methods and Learning Models. Knowledge-Based Systems 81 (2015) 76-97. doi: 10.1016/j.knosys.2015.02.008
  
• [1891] M. Galar, J. Derrac, D. Peralta, I. Triguero, D. Paternain, C. Lopez-Molina, S. García, J.M. Benítez, M. Pagola, E. Barrenechea, H. Bustince, F. Herrera. A Survey of Fingerprint Classification Part II: Experimental Analysis and Ensemble Proposal. Knowledge-Based Systems 81 (2015) 98-116. doi: 10.1016/j.knosys.2015.02.015
  COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes
  
  
• [1892] A. Tejeda-Lorente, J. Bernabé-Moreno, C. Porcel, E. Herrera-Viedma. REFORE: A recommender system for researchers based on bibliometrics. Applied Soft Computing 30 (2015) 778-791. doi: doi:10.1016/j.asoc.2015.02.024
  
• [1893] C. Martínez-Cruz, C. Porcel, J. Bernabé-Moreno, E. Herrera-Viedma. A Model to Represent Users Trust in Recommender Systems using Ontologies and Fuzzy Linguistic Modeling. Information Sciences 311 (2015) 102-118. doi: doi:10.1016/j.ins.2015.03.013
  
• [1897] Ning Xiong, D. Molina, Miguel Leon Ortiz, F. Herrera. A Walk into Metaheuristic for Engineering Optimization: Principles, Methods and Recent Trends. International Journal of Computational Intelligence Systems 8:4 (2015) 606-636. doi: 10.1080/18756891.2015.1046324
  
• [1956] M.R. Ureña, F. Chiclana, H. Fujita, E. Herrera-Viedma. Confidence-consistency driven group decision making approach with incomplete reciprocal intuitionistic preference relations. Knowledge-Based Systems 89 (2015) 86–96. doi: 10.1016/j.knosys.2015.06.020
  
• [1921] D. Peralta, M. Galar, I. Triguero, D. Paternain, S. García, E. Barrenechea, J. M. Benítez, H. Bustince, F. Herrera. A Survey on Fingerprint Minutiae-based Local Matching for Verification and Identification: Taxonomy and Experimental Evaluation. Information Sciences 315 (2015) 67-87. doi: 10.1016/j.ins.2015.04.013
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• [1923] L. D’eer, N. Verbiest, C. Cornelis, L. Godo. A Comprehensive Study of Implicator-Conjunctor Based and Noise-Tolerant Fuzzy Rough Sets: Definitions, Properties and Robustness Analysis. Fuzzy Sets and Systems 275 (2015) 1-38. doi: 10.1016/j.fss.2014.11.018
  
• [1926] I. Triguero, S. Río, V. López, J. Bacardit, J.M. Benítez, F. Herrera. ROSEFW-RF: The winner algorithm for the ECBDL'14 Big Data Competition: An extremely imbalanced big data bioinformatics problem. Knowledge-Based Systems 87 (2015) 69-79. doi: 10.1016/j.knosys.2015.05.027
  
• [1929] L. Septem, C. Bergmeir, F. Herrera, J.M. Benítez. frbs: Fuzzy Rule-Based Systems for Classification and Regression in R. Statistical Software 65:6 (2015). doi: 10.18637/jss.v065.i06
  
• [1931] F.J. Cabrerizo, J.A. Morente-Molinera, I.J. Pérez, J. López-Gijón, E. Herrera-Viedma. A decision support system to develop a quality management in academic digital libraries. Information Sciences 323 (2015) 48-58. doi: 10.1016/j.ins.2015.06.022
  
• [1953] Z. Gong, H. Zang, E. Herrera-Viedma, U. A. Ozturk, X. Xul, C. Xu. The Minimum Cost Consensus Models with Interval Preference Opinions and Their Economic Interpretation. Omega, The Int. Journal of Management Science, 55 (2015) 81-90. doi: 10.1016/j.omega.2015.03.003
  
• [1933] O. Banos, J.A. Moral-Muñoz, I. Diaz-Reyes, M. Arroyo-Morales, M. Damas, E. Herrera-Viedma, C.S. Hong, S. Lee, H. Pomares, I. Rojas, H. Pomares, C. Villalonga. mDurance: a Novel Mobile Health System to Support Trunk Endurance Assessment. Sensors 15 (2015) 13159-13183. doi: 10.3390/s150613159
  
• [1934] A. Cid-López, M.J. Hornos, R.A. Carrasco, E. Herrera-Viedma. A Hybrid Model for Decision-Making in the Information and Communications Technology sector. Technological and Economic Development of Economy 21:5 (2015) 720-737. doi: 10.3846/20294913.2015.1056281
  
• [1937] B. Krawczyk, M. Wozniak, F. Herrera. On the Usefulness of One-Class Classifier Ensembles for Decomposition of Multi-Class Problems. Pattern Recognition 48:12 (2015) 3969-3982. doi: 10.1016/j.patcog.2015.06.001
  
• [1938] R. Montes, A.M. Sánchez, P. Villar, F. Herrera. A web tool to support decision making in the housing market using hesitant fuzzy linguistic term sets. Applied Soft Computing 35 (2015) 949-957. doi: 10.1016/j.asoc.2015.01.030
  
• [1939] D. Peralta, S. Río, S. Ramírez-Gallego, I. Triguero, J.M. Benítez, F. Herrera. Evolutionary Feature Selection for Big Data Classification: A MapReduce Approach. Mathematical Problems in Engineering, vol. 2015, Article ID 246139 (2015) 11 pages. doi: 10.1155/2015/246139
  
• [1947] J.V. Riera, S. Massanet, E. Herrera-Viedma, J. Torrens. Some interesting properties of the fuzzy linguistic model based on discrete fuzzy numbers to manage hesitant fuzzy linguistic information. Applied Soft Computing 36 (2015) 383-391. doi: 10.1016/j.asoc.2015.07.022
  
• [1948] J.A. Morente-Molinera, I.J. Pérez, M.R. Ureña, E. Herrera-Viedma. Building and Managing Fuzzy Ontologies with Heterogeneous Linguistic Information. Knowledge-Based Systems 88 (2015) 154–164. doi: 10.1016/j.knosys.2015.07.035
  
• [1951] D. Galpert, S. Río, F. Herrera, E. Ancede, A. Antunes, G. Agüero-Chapin. An Effective Big Data Supervised Imbalanced Classification Approach for Ortholog Detection in Related Yeast Species. BioMed Research International (2015) 12 pages, Article Id 748681. doi: 10.1155/2015/748681
  
• [1955] F.J. Cabrerizo, F. Chiclana, R. Al-Hmouz, A. Morfeq, A.S. Balamash, E. Herrera-Viedma. Fuzzy decision making and consensus: challenges. Journal of Intelligent & Fuzzy Systems 29:3 (2015) 1109-1118. doi: 10.3233/IFS-151719
  
• [1959] M.J. Cobo, A.G. López-Herrera, E. Herrera-Viedma. A Relational Database Model for Science Mapping Analysis. Acta Polytechnica Hungarica 12:6 (2015) 43-62. doi: 10.12700/APH.12.6.2015.6.3
  
• [1960] A. Cid-López, M. J. Hornos, R. A. Carrasco-González, E. Herrera-Viedma. SICTQUAL: A fuzzy linguistic multi-criteria model to assess the quality of service in the ICT sector from the user perspective. Applied Soft Computing 37 (2015) 897–910. doi: 10.1016/j.asoc.2015.09.019
  
• [1963] L.P.F. Garcia, José A. Sáez, J. Luengo, A.C. Lorena, A.C. de Carvalho, F. Herrera. Using the One-vs-One decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems. Knowledge-Based Systems 90 (2015) 153-164. doi: 10.1016/j.knosys.2015.09.023
  
• [1967] F. Charte, A.J. Rivera, M.J. del Jesus, F. Herrera. MLSMOTE: Approaching Imbalanced Multilabel Learning Through Synthetic Instance Generation. Knowledge-Based Systems 89 (2015) 385-397. doi: 10.1016/j.knosys.2015.07.019
  
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• [1997] E. Herrera-Viedma. Fuzzy sets and fuzzy logic in multi-criteria decision making. The 50th anniversary of prof. Lotfi Zadeh’s theory: Introduction. Technological and Economic Development of Economy 21:5 (2015) 677-683. doi: 10.3846/20294913.2015.1084956
  
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• [2272] DC. Garcia-Ramon, MJ. Luque-Navas, CA. Molina, C. del Val, A: Osuna, S. Vilchez. Identification, sequencing and comparative analysis of pBp15.S plasmid from the newly described entomopathogen Bacillus pumilus 15.1. Journal:Plasmid. 2015 Nov;82:17-27. doi: 10.1016/j.plasmid.2015.09.001
  
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• [2382] E. Herrera-Viedma, J. Bernabé-Moreno, C. Porcel, M.A. Martínez. Solidarity in Social Media: when users abandon their comfort zone - The Charlie Hebdo case. Revista ICONO14 13:2 (2015) 6-22. doi: 10.7195/ri14.v13i2.888
  

2014 (73)

• [1698] J. Derrac, S. García, F. Herrera. Fuzzy Nearest Neighbor Algorithms: Taxonomy, Experimental analysis and Prospects . Information Sciences 260 (2014) 98-119. doi: 10.1016/j.ins.2013.10.038
  COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes
  
  
• [1697] C. García-Martínez, F. Glover, F. J. Rodriguez, M. Lozano, R. Martí. Strategic Oscillation for the Quadratic Multiple Knapsack Problem . Computational Optimization and Applications 58:1 (2014) 161-185. doi: 10.1007/s10589-013-9623-y
  
• [1557] José A. Sáez, M. Galar, J. Luengo, F. Herrera. Analyzing the Presence of Noise in Multi-class Problems: Alleviating its Influence with the One-vs-One Decomposition. Knowledge and Information Systems 38:1 (2014) 179-206. doi: 10.1007/s10115-012-0570-1
  COMPLEMENTARY MATERIAL to the paper
  
  
• [1581] M. Lozano, F. Glover, C. García-Martínez, F. J. Rodriguez, R. Martí. Tabu Search with Strategic Oscillation for the Quadratic Minimum Spanning Tree. IIE Transactions 46:4 (2014) 1-5 .
  
• [1588] V. López, I. Triguero, C.J. Carmona, S. García, F. Herrera. Addressing Imbalanced Classification with Instance Generation Techniques: IPADE-ID. Neurocomputing 126 (2014) 15-28. doi: 10.1016/j.neucom.2013.01.050
  
• [1626] B.R. Campomanes-Álvarez, O. Cordón, S. Damas, O. Ibáñez. Computer-based craniofacial superimposition in forensic identification using soft computing. Journal of Ambient Intelligence and Humanized Computing, 5:5 (2014) 683-697. doi: 10.1007/s12652-012-0168-1
  
• [1637] I.J. Pérez, F.J. Cabrerizo, S. Alonso, E. Herrera-Viedma. A New Consensus Model for Group Decision Making Problems with Non Homogeneous Experts. IEEE Transactions on Systems, Man, and Cybernetics: Systems 44:4 (2014) 494-498. doi: 10.1109/TSMC.2013.2259155
  
• [1638] E. Herrera-Viedma, F.J. Cabrerizo, J. Kacprzyk, W. Pedrycz. A Review of Soft Consensus Models in a Fuzzy Environment. Information Fusion 17 (2014) 4-13. doi: 10.1016/j.inffus.2013.04.002
  
• [1642] I. Palomares, L. Martínez, F. Herrera. A Consensus Model to Detect and Manage Non-Cooperative Behaviors in Large Scale Group Decision Making. IEEE Transactions on Fuzzy Systems 22:3 (2014) 516–530. doi: 10.1109/TFUZZ.2013.2262769
  
• [1646] I. Triguero, José A. Sáez, J. Luengo, S. García, F. Herrera. On the Characterization of Noise Filters for Self-Training Semi-Supervised in Nearest Neighbor Classification. Neurocomputing 132 (2014) 30-41. doi: 10.1016/j.neucom.2013.05.055
  
• [1648] P. Shelokar, A. Quirin, O. Cordón. Three-Objective Subgraph Mining using Multiobjective Evolutionary Programming. Journal of Computer and System Sciences 80:1 (2014) 16-26.
  
• [1660] S. Massanet, J.V. Riera, J. Torrens, E. Herrera-Viedma. A new linguistic computational model based on discrete fuzzy numbers for computing with words. Information Sciences 258 (2014) 277-290. doi: 10.1016/j.ins.2013.06.055
  
• [1659] I. Palomares, L. Martínez, F. Herrera. MENTOR: A Graphical Monitoring Tool of Preferences Evolution in Large-Scale Group Decision Making. Knowledge-based Systems 58 (2014) 66–74. doi: 10.1016/j.knosys.2013.07.003
  
• [1665] C. García-Martínez, F. J. Rodriguez, M. Lozano. Tabu-Enhanced Iterated Greedy Algorithm: A Case Study in the Quadratic Multiple Knapsack Problem. European Journal of Operational Research 232:3 (2014) 454–463. doi: 10.1016/j.ejor.2013.07.035
  
• [1667] M. Restrepo, C. Cornelis, J. Gómez. Duality, Conjugacy and Adjointness of Approximation Operators in Covering Based Rough Sets. International Journal of Approximate Reasoning 55:1 (2014) 469-485. doi: 10.1016/j.ijar.2013.08.002
  
• [1670] D. Peralta, I. Triguero, R. Sanchez-Reillo, F. Herrera, J.M. Benítez. Fast Fingerprint Identification for Large Databases. Pattern Recognition 47:2 (2014) 588–602. doi: 10.1016/j.patcog.2013.08.002
  COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes
  
  
• [1671] C. Cornelis, J. Medina, N. Verbiest. Multi-adjoint fuzzy rough sets: Definition, properties and attribute selection. International Journal of Approximate Reasoning 55:1 (2014) 412-426. doi: 10.1016/j.ijar.2013.09.007
  
• [1672] V. López, A. Fernandez, F. Herrera. On the Importance of the Validation Technique for Classification with Imbalanced Datasets: Addressing Covariate Shift when Data is Skewed. Information Sciences 257 (2014) 1-13. doi: 10.1016/j.ins.2013.09.038
  
• [1673] D. Martín, A. Rosete, J. Alcalá-Fdez, F. Herrera. QAR-CIP-NSGA-II: A New Multi-Objective Evolutionary Algorithm to Mine Quantitative Association Rules. Information Sciences 258 (2014) 1-28. doi: 10.1016/j.ins.2013.09.009
  
• [1674] D. Martín, A. Rosete, J. Alcalá-Fdez, F. Herrera. A New Multi-Objective Evolutionary Algorithm for Mining a Reduced Set of Interesting Positive and Negative Quantitative Association Rules. IEEE Transactions on Evolutionary Computation 18:1 (2014) 54-69. doi: 10.1109/TEVC.2013.2285016
  
• [1677] M.J. Cobo, F. Chiclana, A. Collop, J. de Oña, E. Herrera-Viedma. A Bibliometric Analysis of the Intelligent Transportation Systems Research Based on Science Mapping. IEEE Transactions on Intelligent Transportation Systems, 11:2, pp. 901-908 (2014). doi: 10.1109/TITS.2013.2284756
  
• [1678] M.A. Martínez, M. Herrera, J. López-Gijón, E. Herrera-Viedma. H-Classics: Characterizing the Concept of Citation Classics Through H-index. Scientometrics, 98 (2014) 1971-1983. doi: 10.1007/s11192-013-1155-9
  
• [1708] F. Charte Ojeda, A. Rivera, M.J. del Jesus, F. Herrera. LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multi-label Classification. IEEE Transactions on Neural Networks and Learning Systems, 25:10 (2014) 1842-1854. doi: 10.1109/TNNLS.2013.2296501
  
• [1687] J.M. García-Torres, S. Damas, O. Cordón, J. Santamaría. A case study of innovative population-based algorithms in 3D modeling: Artificial bee colony, biogeography-based optimization, harmony search. Expert Systems with Applications 41:4 (2014) 1750-1762.
  
• [1702] A. Tejeda-Lorente, C. Porcel, E. Peis, R. Sanz, E. Herrera-Viedma. A quality based recommender system to disseminate information in a University Digital Library. Information Sciences 261 (2014) 52-69. doi: 10.1016/j.ins.2013.10.036
  
• [1742] S. Río, V. López, J.M. Benítez, F. Herrera. On the use of MapReduce for Imbalanced Big Data using Random Forest. Information Sciences 285 (2014) 112-137. doi: 10.1016/j.ins.2014.03.043
  COMPLEMENTARY MATERIAL to the paper
  
  
• [1703] P.D. Gutiérrez, M. Lastra, F. Herrera, J.M. Benítez. A high performance fingerprint matching system for large databases based on GPU. IEEE Transactions on Information Forensics and Security 9:1 (2014) 62-71. doi: 10.1109/TIFS.2013.2291220
  
• [1706] B. Lacroix, D. Molina, F. Herrera. Region based memetic algorithm for real-parameter optimisation. Information Sciences, 262 (2014) 15-31. doi: 10.1016/j.ins.2013.11.032
  
• [1709] M, Galar, A. Fernandez, E. Barrenechea, F. Herrera. Empowering difficult classes with a Similarity-based aggregation in multi-class classification problems. Information Sciences 264 (2014) 135-157. doi: 10.1016/j.ins.2013.12.053
  
• [1791] José A. Sáez, J. Derrac, J. Luengo, F. Herrera. Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers. Pattern Recognition 47:12 (2014) 3941–3948. doi: 10.1016/j.patcog.2014.06.012
  COMPLEMENTARY MATERIAL to the paper
  
  
• [1721] C. Bergmeir, M. Costantini, J.M. Benítez. On the usefulness of cross-validation for directional forecast evaluation. Computational Statistics and Data Analysis 76 (2014) 132-143. doi: 10.1016/j.csda.2014.02.001
  
• [1722] J. Otero, L. Sánchez, I. Couso, A. Palacios. Bootstrap analysis of multiple repetitions of experiments using an interval valued multiple comparison procedure. Journal of Computer and System Sciences 80 (2014) 88-100 .
  
• [1848] J. Otero, A. Palacios, R. Suarez, L. Junco, I. Couso, L. Sanchez. A procedure for extending input selection algorithms to low quality data in modelling problems with application to the automatic grading of uploaded assignments. The Scientific World Journal. doi: 10.115/2014/468405
  
• [1729] Liao Tianjun, D. Molina, Marco A. Montes de Oca, Thomas Stützle. A Note on Bound Constraints Handling for the IEEE CEC’05 Benchmark Function Suite. Evolutionary Computation 22:2 (2014) 351-359. doi: 10.1162/EVCO_a_00120
  
• [1732] M.J. Gacto, M. Galende, R. Alcalá, F. Herrera. METSK-HDe: A Multiobjective Evolutionary Algorithm to learn accurate TSK-fuzzy Systems in High-Dimensional and Large-Scale Regression Problems. Information Sciences 276 (2014) 63-79. doi: 10.1016/j.ins.2014.02.047
  
• [1735] J.A. Moral-Muñoz, M.J. Cobo, E. Peis, M. Arroyo-Morales, E. Herrera-Viedma. Analyzing the research in Integrative & Complementary Medicine by means of science mapping. Complementary Therapies in Medicine, 22:2, pp. 409-418 (2014). doi: 10.1016/j.ctim.2014.02.003
  
• [1736] D.S. Tarragó, C. Cornelis, R. Bello, F. Herrera. A Multi-Instance Learning Wrapper based on the Rocchio Classifier for Web Index Recommendation. Knowledge-Based Systems 59 (2014) 173-181. doi: 10.1016/j.knosys.2014.01.008
  
• [1740] D. Peralta, M. Galar, I. Triguero, O. Miguel-Hurtado, J.M. Benítez, F. Herrera. Minutiae Filtering to Improve Both Efficacy and Efficiency of Fingerprint Matching Algorithms. Engineering Applications of Artificial Intelligence, 32 (2014) 37-53. doi: 10.1016/j.engappai.2014.02.016
  
• [1741] Nicolás Robinson-García, Daniel Torres-Salinas, Emilio Delgado López-Cózar, F. Herrera. An insight into the importance of national university rankings in an international context: The case of the I-UGR Rankings of Spanish universities. Scientometrics 101 (2014) 1309–1324. doi: 10.1007/s11192-014-1263-1
  
• [1758] D. Gomez-Lorente, I. Triguero, C. Gil, O. Rabaza. Multi-Objective Evolutionary Algorithms for the Design of Grid- Connected Solar Tracking Systems. International Journal of Electrical Power and Energy Systems, 61 (2014) 371-379. doi: 10.1016/j.ijepes.2014.03.064
  
• [1760] F.J. Cabrerizo, M.R. Ureña, W. Pedrycz, E. Herrera-Viedma. Building consensus in group decision making with an allocation of information granularity. Fuzzy Sets and Systems 255 (2014) 115-127. doi: 10.1016/j.fss.2014.03.016
  
• [1761] B. Esteban, A. Tejeda-Lorente, C. Porcel, M. Arroyo, E. Herrera-Viedma. TPLUFIB-WEB: A fuzzy linguistic Web system for treatment and prevention of low back pain. Knowledge-based Systems, 67 (2014) 429-438. doi: 10.1016/j.knosys.2014.03.004
  
• [1763] R.M. Rodríguez, L. Martínez, V. Torra, Z.S. Xu, F. Herrera. Hesitant Fuzzy Sets: State of the Art and Future Directions. International Journal of Intelligent Systems 29 (2014) 495-524. doi: 10.1002/int.21654
  
• [1764] I. Palomares, F.J. Estrella, L. Martínez, F. Herrera. Consensus under a fuzzy context: Taxonomy, analysis framework AFRYCA and experimental case of study. Information Fusion 20 (2014) 252-271. doi: 10.1016/j.inffus.2014.03.002
  
• [1766] C.J. Carmona, P. González, M.J. del Jesus, F. Herrera. Overview on evolutionary subgroup discovery: analysis of the suitability and potential of the search performed by evolutionary algorithms. WIREs Data Mining Knowledge Discovevery 4 (2014), 87-103. doi: 10.1002/widm.1118
  
• [1771] M. Galende, M.J. Gacto, G. Sainz, R. Alcalá. Comparison and Design of Interpretable Linguistic vs. Scatter FRBSs: GM3M Generalization and New Rule Meaning Index (RMI) for Global Assessment and Local Pseudo-Linguistic Representation. Information Sciences 282 (2014) 190-213. doi: 10.1016/j.ins.2014.05.023
  
• [1772] V. Bolón-Canedo, N. Sánchez-Maroño, A. Alonso-Betanzos, J.M. Benítez, F. Herrera. A review of microarray datasets and applied feature selection methods. Information Sciences 282 (2014) 111-135. doi: 10.1016/j.ins.2014.05.042
  
• [1773] N. Verbiest, E. Ramentol, C. Cornelis, F. Herrera. Preprocessing Noisy Imbalanced Datasets using SMOTE enhanced with Fuzzy Rough Prototype Selection. Applied Soft Computing 22 (2014) 511-517. doi: 10.1016/j.asoc.2014.05.023
  
• [1774] C. Cobos, H. Muñoz-Collazos, R. Urbano-Muñoz, M. Mendoza, E. Leon, E. Herrera-Viedma. Clustering of Web Search Results based on the Cuckoo Search Algorithm and Balanced Bayesian Information Criterion. Information Sciences 281 (2014) 248–264. doi: 10.1016/j.ins.2014.05.047
  
• [1782] A. Fernandez, D. Peralta, J.M. Benítez, F. Herrera. E-learning and educational data mining in cloud computing: an overview. International Journal of Learning Technology, 9:1 (2014) 25-52.
  
• [1781] A. Valsecchi, S. Damas, J. Santamaría, L. Marrakchi-Kacem. Intensity-based image registration using scatter search. Artificial Intelligence in Medicine 60:3 (2014), 151-163.
  
• [1789] F.J. Estrella, M. Espinilla, F. Herrera, L. Martínez. FLINTSTONES: A fuzzy linguistic decision tools enhancement suite based on the 2-tuple linguistic model and extensions. Information Sciences 280 (2014) 152-170. doi: 10.1016/j.ins.2014.04.049
  
• [1794] J. Derrac, S. García, S. Hui, P. N. Suganthan, F. Herrera. Analyzing convergence performance of evolutionary algorithms: A statistical approach. Information Sciences 289 (2014) 41-58. doi: 10.1016/j.ins.2014.06.009
  COMPLEMENTARY MATERIAL to the paper
  
  
• [1810] A. Fernandez, S. Río, V. López, A. Bawakid, M.J. del Jesus, J.M. Benítez, F. Herrera. Big Data with Cloud Computing: An Insight on the Computing Environment, MapReduce and Programming Frameworks. WIREs Data Mining and Knowledge Discovery 4:5 (2014) 380-409. doi: 10.1002/widm.1134
  
• [1816] M. Fazzolari, R. Alcalá, F. Herrera. A Multi-Objective Evolutionary Method for Learning Granularities based on Fuzzy Discretization to Improve the Accuracy-Complexity trade-off of Fuzzy Rule-Based Classification Systems: D-MOFARC Algorithm. Applied Soft Computing 24 (2014) 470-481.
  
• [1817] L. S. Riza, Andrzej Janusz, C. Bergmeir, C. Cornelis, F. Herrera, Dominik Slezak, J.M. Benítez. Implementing algorithms of rough set theory and fuzzy rough set theory in the R package "RoughSets". Information Sciences 287 (2014) 68-89.
  
• [1825] A. Palacios, K. Trawinski, O. Cordón, L. Sánchez. Cost-sensitive Learning of Fuzzy Rules for Imbalanced Classification Problems using FURIA. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems, 22:5 (2014) 643–675. doi: 10.1142/S0218488514500330
  
• [1838] H.M. Kammoun, I. Kallel, J. Casillas, A. Abraham, A.M. Alimi. Adapt-Traf: An adaptive multiagent road traffic management system based on hybrid ant-hierarchical fuzzy model. Transportation Research Part C: Emerging Technologies 42 (2014) 147–167. doi: 10.1016/j.trc.2014.03.003
  
• [1861] B.R. Campomanes-Álvarez, O. Ibáñez, F. Navarro, I. Alemán, M. Botella, S. Damas, O. Cordón. Computer Vision and Soft Computing for Automatic Skull-Face Overlay in Craniofacial Superimposition. Forensic Science International 245 (2014) 77-86.
  
• [1895] F. Herrera. Big data: Procesando los datos en la sociedad digital. Revista de Física 28:4 (2014) 40-44.
  
• [1922] M. Restrepo, C. Cornelis, J. Gómez. Partial Order Relation for Approximation Operators in Covering Based Rough Sets. Information Sciences 284 (2014) 44-59. doi: 10.1016/j.ins.2014.06.032
  
• [1977] J. Castro, R.M. Rodríguez, L. Martínez. Weighting of Features in Content-Based Filtering with Entropy and Dependence Measures. International Journal of Computational Intelligence Systems, 7:1 (2014) 80-89. doi: 10.1080/18756891.2013.859861
  
• [2059] B. Krawczyk, M. Wozniak, F. Herrera. Weighted one-class classification for different types of minority class examples in imbalanced data. Computational Intelligence and Data Mining (CIDM), 2014 IEEE Symposium on Orlando, FL. 9-12 Dec. 2014. 337-344. doi: 10.1109/CIDM.2014.7008687
  
• [2432] S. García, J. Derrac, S. Ramírez-Gallego, F. Herrera. On the statistical analysis of the parameters’ trend in a machine learning algorithm. Progress in Artificial Intelligence 3:1 (2014) 51-53. doi: 10.1007/s13748-014-0043-8
  
• [2219] R. Montes, M. Gea, C. Dondi. Engaging OER at Universities. Revista Educación Mediática y Aplicación Didáctica de las TIC 3:2 (2014) 7-28.
  
• [2220] R. Montes, M. Gea, J. Haywood. Open Learning Recognition in Traditional Universities. Lifelong education: the XXI century journal 1:5 (2014).
  
• [2221] R. Montes, M. Gea, B. Rojas, R. Bergaz. Generating lifelong-learning communities and branding with Massive Open Online Courses. Information Resources Management Journal 27:2 (2014) 27-46.
  
• [2222] V. Gámiz, R. Montes, M.C. Pérez. Self-assessment via a blended-learning strategy to improve performance in an accounting subject. RUSC. Universities and Knowledge Society Journal 11:2 (2014) 41-54.
  
• [2224] M. Gea, R. Montes, B. Rojas, R. Bergaz. Comunidades activas de aprendizaje: hacia la formación abierta en las universidades. Revista Iberoamericana de Tecnologías del Aprendizaje (IEEE - RITA) 2:1 (2014) 3-10.
  
• [2256] H. Liu, R.M. Rodriguez. A fuzzy envelope for hesitant fuzzy linguistic term set and its application to multicriteria decision making. Information Sciences 258 (2014) 220-238. doi: 10.1016/j.ins.2013.07.027
  
• [2259] C. del Val, Bondar L. Bondar AN. Coupling between inter-helical hydrogen bonding and water dynamics in a proton transporter.. Journal:Journal of Structural Biology 2014 Apr;186(1):95-111. doi: 10.1016/j.jsb.2014.02.010
  
• [2262] J. Arnedo, R. Romero Zaliz, I. Zwir, C. del Val. A multiobjective method for robust identification of bacterial small non-coding RNAs. Bioinformatics. 2014 Oct 15;30(20):2875-82. doi: 10.1093/bioinformatics/btu398
  
• [2381] M.A. Martínez, M. Díaz, A. Lima, M. Herrera, E. Herrera-Viedma. Un Análisis Bibliométrico de la Producción Académica Española en Trabajo Social según el Web of Science. Cuadernos de Trabajo Social 27:2 (2014) 429-438.
  

2013 (57)

• [1304] J G Moreno-Torres, X. Llorà, D. E. Goldberg, R. Bhargava. Repairing Fractures between Data using Genetic Programming-based Feature Extraction: A Case Study in Cancer Diagnosis. Information Sciences 222 (2013) 805-823.
  
• [1447] P. Shelokar, A. Quirin, O. Cordón. MOSubdue: A Pareto Dominance-based Multiobjective Subdue Algorithm for Frequent Subgraph Mining. Knowledge and Information Systems 34:1 (2013) 75-108. doi: 10.1007/s10115-011-0452-y
  
• [1469] S. García, J. Luengo, José A. Sáez, V. López, F. Herrera. A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning. IEEE Transactions on Knowledge and Data Engineering 25:4 (2013) 734-750. doi: 10.1109/TKDE.2012.35
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• [1539] José A. Sáez, J. Luengo, F. Herrera. Predicting Noise Filtering Efficacy with Data Complexity Measures for Nearest Neighbor Classification. Pattern Recognition 46:1 (2013) 355-364. doi: 10.1016/j.patcog.2012.07.009
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• [1507] J. Santamaría, S. Damas, O. Cordón, A. Escámez. Self-adaptive evolution: towards new parameter free image registration methods. IEEE Transactions on Evolutionary Computation 17:3 (2013) 545-557.
  
• [1521] M. Fazzolari, R. Alcalá, Y. Nojima, H. Ishibuchi, F. Herrera. A Review of the Application of Multi-Objective Evolutionary Fuzzy Systems: Current Status and Further Directions. IEEE Transactions on Fuzzy Systems, 21:1 (2013) 45-65.
  COMPLEMENTARY MATERIAL to the paper: links to the papers with doi, new contributions, etc
  
  
• [1537] J. Derrac, N. Verbiest, S. García, C. Cornelis, F. Herrera. On the use of Evolutionary Feature Selection for Improving Fuzzy Rough Set Based Prototype Selection. Soft Computing 17:2 (2013) 223-238. doi: 10.1007/s00500-012-0888-3
  
• [1544] S. Alonso, I.J. Pérez, F.J. Cabrerizo, E. Herrera-Viedma. A Linguistic Consensus Model for Web 2.0 Communities. Applied Soft Computing 13:1 (2013) 149-157. doi: 10.1016/j.asoc.2012.08.009
  
• [1554] V. López, A. Fernandez, M.J. del Jesus, F. Herrera. A Hierarchical Genetic Fuzzy System Based On Genetic Programming for Addressing Classification with Highly Imbalanced and Borderline Data-sets. Knowledge-Based Systems 38 (2013) 85-104. doi: 10.1016/j.knosys.2012.08.025
  
• [1558] F. Chiclana, J.M. Tapia Garcia, M.J. Del Moral, E. Herrera-Viedma. A Statistical Comparative Study of Different Similarity Measures of Consensus in Group Decision Making. Information Sciences 221 (2013) 110–123.
  
• [1561] R. García, J.M. Benítez, G.I. Sainz-Palmero. FRASel: A Consensus of feature ranking methods for time series modelling. Soft Computing, Volume 17, Issue 8, pp 1489-1510.
  
• [1562] G. Hurtado, S. Schockaert, C. Cornelis, H. Naessens. Using Semi-Structured Data for Assessing Research Paper Similarity. Information Sciences 221:1 (2013) 245-261. doi: /10.1016/j.ins.2012.09.044
  
• [1563] A. Orriols-Puig, F.J. Martínez-López, J. Casillas, N. Lee. A soft-computing-based method for the automatic discovery of fuzzy rules in databases: Uses for academic research and management support in marketing. Journal of Business Research 66:9 (2013) 1332-1337. doi: 10.1016/j.jbusres.2012.02.033
  
• [1564] A.D. Benítez, J. Casillas. Multi-Objective Genetic Learning of Serial Hierarchical Fuzzy Systems for Large-Scale Problems. Soft Computing 17:1 (2012) 165-194. doi: 10.1007/s00500-012-0909-2
  
• [1566] N. Bova, O. Ibáñez, O. Cordón. Image segmentation using Extended Topological Active Nets optimized by Scatter Search. IEEE Computational Intelligence Magazine 8:1 (2013) 16-32.
  
• [1567] E. Bermejo, O. Cordón, S. Damas, J. Santamaría. Quality time-of-flight range imaging for feature-based registration using bacterial foraging. Applied Soft Computing 13:6 (2013) 3178–3189.
  
• [1570] D. Torres-Salinas, N. Robinson-García, E. Jiménez-Contreras, F. Herrera, E. Delgado López-Cózar. On the Use of Biplot Analysis for Multivariate Bibliometric and Scientific Indicators. Journal of the American Society for Information Science and Technology 64:7 (2013) 1468-1479.
  
• [1574] L. Sanchez, I. Couso, A. Palacios, J. Palacios. A methodology for exploiting the tolerance for imprecision in genetic fuzzy system and its application to characterization of rotor blade learning edge materials. Mechanical System and Signal Processing 37:1-2 (2013) 76-91. doi: 10.1016/j.ymssp.2012.02.009
  
• [1578] I.J. Pérez, R. Wikström, J. Mezei, C. Carlsson, E. Herrera-Viedma. A New Consensus Model for Group Decision Making Using Fuzzy Ontology. Soft Computing 17:9 (2013) 1617-1627. . doi: 10.1007/s00500-012-0975-5
  
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