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Special Issue Cover

A new special issue on Fuzzy Approaches in Preference Modelling, Decision Making and Applications (International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems [IJUFKS]) has been edited by F. Chiclana, E. Herrera-Viedma, S. Alonso, F. Herrera.

 

               EFDAMIS Journal Publications

Number Of Publications: 186 Jump to Graph

Jump to Year: 2013 (20), 2012 (30), 2011 (19), 2010 (19), 2009 (21), 2008 (10), 2007 (14), 2006 (2), 2005 (5), 2004 (4), 2003 (4), 2002 (5), 2001 (8), 2000 (4), 1999 (5), 1998 (5), 1997 (5), 1996 (2), 1995 (3), 1994 (1)

Bolita Year 2013 (20):

Bolita[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. COMPLEMENTARY MATERIAL to the paper here. iconPdf.png

Bolita[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 doi: 10.1109/TFUZZ.2012.2201338. COMPLEMENTARY MATERIAL to the paper here: links to the papers with doi, new contributions, etc.. iconPdf.png

Bolita[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. iconCualquiera.png iconPdf.png

Bolita[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. iconPdf.png

Bolita[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. iconPdf.png

Bolita[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. iconPdf.png

Bolita[1594] A. Fernandez, V. López, M. Galar, M.J. del Jesus, F. Herrera, Analysing the Classification of Imbalanced Data-sets with Multiple Classes: Binarization Techniques and Ad-Hoc Approaches. Knowledge-Based Systems 42 (2013) 97-110, doi: 10.1016/j.knosys.2013.01.018. iconPdf.png

Bolita[1625] P. Shelokar, A. Quirin, O. Cordón, A Multiobjective Evolutionary Programming Framework for Graph-based Data Mining. Information Sciences 273:1 (2013) 118–136, doi: 10.1016/j.ins.2013.02.014. iconPdf.png

Bolita[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. iconPdf.png

Bolita In Press:

Bolita[1634] N. Verbiest, C. Cornelis, F. Herrera, FRPS: A Fuzzy Rough Prototype Selection method. Pattern Recognition, doi: 10.1016/j.patcog.2013.03.004, in press (2013).

Bolita[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, in press (2013).

Bolita[1635] R. M. Rodriguez, L. Martínez, F. Herrera, A Group Decision Making Model Dealing with Comparative Linguistic Expressions based on Hesitant Fuzzy Linguistic Term Sets. Information Sciences, in press (2013).

Bolita[1641] M. Galar, A. Fernandez, E. Barrenechea, F. Herrera, EUSBoost: Enhancing Ensembles for Highly Imbalanced Data-sets by Evolutionary Undersampling. Pattern Recognition, in press (2013).

Bolita[1584] R.A. Carrasco, F. Muñoz-Leiva, M. Hornos, A Multidimensional Data Model using the Fuzzy Model based on the Semantic Translation. International Journal Information Systems Frontiers, doi: 10.1007/s10796-012-9398-1, in press (2013).

Bolita[1643] M. Galar, A. Fernandez, E. Barrenechea, H. Bustince, F. Herrera, Dynamic Classifier Selection for One-vs-One Strategy: Avoiding Non-Competent Classifiers. Pattern Recognition, in press (2013).

Bolita[1587] J. Sanz, A. Fernandez, H. Bustince, F. Herrera, IVTURS: a linguistic fuzzy rule-based classification system based on a new Interval-Valued fuzzy reasoning method with TUning and Rule Selection. IEEE Transactions on Fuzzy Systems, in press (2013).

Bolita[1588] V. López, I. Triguero, C.J. Carmona, S. García, F. Herrera, Addressing Imbalanced Classification with Instance Generation Techniques: IPADE-ID. Neurocomputing, in press (2013).

Bolita[1629] K. Trawinski, O. Cordón, L. Sánchez, A. Quirin, A Genetic Fuzzy Linguistic Combination Method for Fuzzy Rule-Based Multiclassifiers. IEEE Transactions on Fuzzy Systems, in press (2013).

Bolita[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, doi: 10.1016/j.jbusres.2012.02.033., in press (2013). iconPdf.png

Bolita[1630] D.P. Pancho, J.M. Alonso, O. Cordón, A. Quirin, L. Magdalena, FINGRAMS: Visual Representations of Fuzzy Rule-Based Inference for Expert Analysis of Comprehensibility. IEEE Transactions on Fuzzy Systems, in press (2013).

Bolita Year 2012 (30):

Bolita[1518] J. A. García, R. Rodriguez-Sánchez, J. Fdez-Valdivia, D. Torres-Salinas, F. Herrera , Ranking of research output of universities on the basis of the multidimensional prestige of influential fields: Spanish universities as a case of study. Scientometrics 93:3 (2012) 681-698 doi: 10.1007/s11192-012-0740-7. iconPdf.png

Bolita[1583] R.A. Carrasco, F. Muñoz-Leiva, J. Sánchez-Fernández, F. J. Liébana-Cabanillas, A model for the integration of e-financial services questionnaires with SERVQUAL scales under fuzzy linguistic modeling. Expert Systems with Applications 39:14 (2012) 11535-11547, doi: 10.1016/j.eswa.2012.03.055. iconPdf.png

Bolita[1506] J.L. Aznarte M., J. Alcalá-Fdez, A. Arauzo, J.M. Benítez, Financial Time Series Forecasting with a Bio-inspired Fuzzy Model. Expert Systems with Applications 39:16 (2012) 12302–12309. iconPdf.png

Bolita[1434] E. Ramentol, Y. Caballero, R. Bello, F. Herrera, SMOTE-RSB*: A Hybrid Preprocessing Approach based on Oversampling and Undersampling for High Imbalanced Data-Sets using SMOTE and Rough Sets Theory. Knowledge and Information Systems 33:2 (2012) 245-265, doi: 10.1007/s10115-011-0465-6. iconPdf.png

Bolita[1446] K. Trawinski, O. Cordón, A. Quirin, A Study on the Use of Multiobjective Genetic Algorithms for Classifier Selection in FURIA-based Fuzzy Multiclassifiers. International Journal of Computational Intelligence Systems 5:2 (2012) 231-253. iconPdf.png

Bolita[1525] C. Carmona, J. Luengo, P. González, M.J. Del Jesus, An analysis on the use of pre-processing methods in evolutionary fuzzy systems for subgroup discovery. Expert Systems wit Applications 39 (2012) 11404–11412, doi: 10.1016/j.eswa.2012.04.029. iconPdf.png

Bolita[1522] J. Sanz, A. Fernandez, H. Bustince, F. Herrera, IIVFDT: Ignorance Functions based Interval-Valued Fuzzy Decision Tree with Genetic Tuning. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 20:2 (2012) 1-30, doi: 10.1142/S0218488512500195. iconPdf.png

Bolita[1514] J. Derrac, I. Triguero, S. García, F. Herrera, Integrating Instance Selection, Instance Weighting and Feature Weighting for Nearest Neighbor Classifiers by Co-evolutionary Algorithms. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics 42:5 (2012) 1383-1397, doi: 10.1109/TSMCB.2012.2191953 COMPLEMENTARY MATERIAL to the paper here: datasets, experimental results and source codes. iconPdf.png

Bolita[1542] D. Docampo, F. Herrera, T. Luque-Martínez, D. Torres-Salinas, Efecto de la agregación de universidades españolas en el Ranking de Shanghai (ARWU): caso de las comunidades autónomas y los campus de excelencia. El profesional de la información 21:4 (2012) 428-432, doi: 10.3145/epi.2012.jul.16. iconPdf.png

Bolita[1530] I. Triguero, J. Derrac, S. García, F. Herrera, Integrating a Differential Evolution Feature Weighting scheme into Prototype Generation. Neurocomputing 97 (2012) 332-343, doi: 10.1016/j.neucom.2012.06.009. iconPdf.png

Bolita[1495] D. Gómez-Lorente, I. Triguero, C. Gil, A. Espín Estrella, Evolutionary Algorithms for the Design of Grid-connected PV-systems. Expert Systems with Applications 39:9 (2012) 8086-8094, doi: 10.1016/j.eswa.2012.01.159 . iconPdf.png

Bolita[1442] H. Bustince, M. Pagola, R. Mesiar, E. Hullermeier, F. Herrera, Grouping, Overlap and Generalized Bi-Entropic Functions for Fuzzy Modeling of Pairwise Comparisons. IEEE Transactions on Fuzzy Systems 20:3 (2012) 405-415, doi: 10.1109/TFUZZ.2011.2173581. iconPdf.png

Bolita[1422] M. Galar, A. Fernandez, E. Barrenechea, H. Bustince, F. Herrera, A Review on Ensembles for Class Imbalance Problem: Bagging, Boosting and Hybrid Based Approaches. IEEE Transactions on System, Man and Cybernetics - Part C: Applications and Reviews 42:4 (2012) 463-484 doi: 10.1109/TSMCC.2011.2161285. iconPdf.png

Bolita[1485] V. López, A. Fernandez, J. G. Moreno-Torres, F. Herrera, Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics. Expert Systems with Applications 39:7 (2012) 6585-6608, doi: 10.1016/j.eswa.2011.12.043. iconPdf.png

Bolita[1419] F. Chávez, F. Fernández, M.J. Gacto, R. Alcalá, Automatic Laser Pointer Detection Algorithm for Environment Control Device Systems Based on Template Matching and Genetic Tuning of Fuzzy Rule-Based Systems. International Journal of Computational Intelligence Systems 5:2 (2012) 368-386, doi: 10.1080/18756891.2012.685327. iconPdf.png

Bolita[1616] B. Van Gasse, G. Deschrijver, C. Cornelis, E. E. Kerre, The Standard Completeness of Interval-Valued Monoidal t-Norm Based Logic. Information Sciences 189:1 (2012) 63-76, http://dx.doi.org/10.1016/j.ins.2011.11.043 . iconPdf.png

Bolita[1430] J. Luengo, José A. Sáez, F. Herrera, Missing data imputation for Fuzzy Rule Based Classifi cation Systems. Soft Computing 16 (2012) 863–881 doi: 10.1007/s00500-011-0774-4 . iconPdf.png

Bolita[1523] P. Villar, A. Fernandez, R.A. Carrasco, F. Herrera, Feature Selection and Granularity Learning in Genetic Fuzzy Rule-Based Classi cation Systems for Highly Imbalanced Data-Sets. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 20:3 (2012) 369-397, doi: S0218488512500195. iconPdf.png

Bolita[1428] J. Derrac, C. Cornelis, S. García, F. Herrera , Enhancing Evolutionary Instance Selection Algorithms by means of Fuzzy Rough Set based Feature Selection. Information Sciences 186:1 (2012) 73-92, doi: 10.1016/j.ins.2011.09.027 . iconPdf.png

Bolita[1372] S. García, J. Derrac, I. Triguero, C.J. Carmona, F. Herrera, Evolutionary-Based Selection of Generalized Instances for Imbalanced Classification. Knowledge Based Systems 25:1 (2012) 3-12 doi: 10.1016/j.knosys.2011.01.012. iconPdf.png

Bolita[1328] M.J. Gacto, R. Alcalá, F. Herrera, A Multi-Objective Evolutionary Algorithm for an Effective Tuning of Fuzzy Logic Controllers in Heating, Ventilating and Air Conditioning Systems. Applied Intelligence 36:2 (2012) 330-347, doi: 10.1007/s10489-010-0264-x . iconPdf.png

Bolita[1429] J. Luengo, F. Herrera, Shared Domains of Competence of Approximative Models using Measures of Separability of Classes. Information Sciences 185:1 (2012) 43-65 doi: 10.1016/j.ins.2011.09.022 . iconPdf.png

Bolita[1336] F. Chávez, F. Fernández, R. Alcalá, J. Alcalá-Fdez, G. Olague, F. Herrera, Hybrid Laser Pointer Detection Algorithm Based on Template Matching and Fuzzy Rule-Based Systems for Domotic Control in Real Home Enviroments. Applied Intelligence 36:2 (2012) 407-423, doi: 10.1007/s10489-010-0268-6. iconPdf.png

Bolita[1443] A. Alvarez-Alvarez, G. Trivino, O. Cordón, Human Gait Modeling Using a Genetic Fuzzy Finite State Machine. IEEE Transactions on Fuzzy Systems 20:2 (2012) 205-223, doi: 10.1109/TFUZZ.2011.2171973. iconPdf.png

Bolita[1365] I. Triguero, J. Derrac, S. García, F. Herrera, A Taxonomy and Experimental Study on Prototype Generation for Nearest Neighbor Classification. IEEE Transactions on Systems, Man, and Cybernetics--Part C: Applications and Reviews 42 (1) (2012) 86-100, doi: 10.1109/TSMCC.2010.2103939. COMPLEMENTARY MATERIAL to the paper here: datasets, experimental results and source codes. iconPdf.png

Bolita[1519] L. Martínez, F. Herrera, An overview on the 2-tuple linguistic model for Computing with Words in Decision Making: Extensions, applications and challenges. Information Sciences 207 (2012) 1-18 doi: 10.1016/j.ins.2012.04.025. iconPdf.png

Bolita[1409] S. García, J. Derrac, J.R. Cano, F. Herrera, Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study. IEEE Transactions on Pattern Analysis and Machine Intelligence 34:3 (2012) 417-435, doi: 10.1109/TPAMI.2011.142 COMPLEMENTARY MATERIAL to the paper here: datasets, experimental results and source codes. iconPdf.png

Bolita[1408] J. Luengo, S. García, F. Herrera, On the choice of the best imputation methods for missing values considering three groups of classification methods. Knowledge and Information Systems 32:1 (2012) 77-108, doi:10.1007/s10115-011-0424-2 COMPLEMENTARY MATERIAL to the paper here: Software, data sets, results and methods description. iconPdf.png

Bolita[1241] E. Pérez, M. Posada, F. Herrera, Analysis of New Niching Genetic Algorithms for Finding Multiple Solutions in the Job Shop Scheduling. Journal of Intelligent Manufacturing 23:3 (2012) 341-356, doi: 10.1007/s10845-010-0385-4. iconPdf.png

Bolita[1398] A. Palacios, M.J. Gacto, J. Alcalá-Fdez, Mining Fuzzy Association Rules from Low Quality Data. Soft Computing 16:5 (2012) 883-901. doi: 10.1007/s00500-011-0775-3. iconPdf.png

Bolita Year 2011 (19):

Bolita[1358] A. Orriols-Puig, J. Casillas, Fuzzy knowledge representation study for incremental learning in data streams and classification problems. Soft Computing - A Fusion of Foundations, Methodologies and Applications 15:12 (2011) 2389-2414, doi: 10.1007/s00500-010-0668-x. iconPdf.png

Bolita[1329] R. Alcalá, Y. Nojima, F. Herrera, H. Ishibuchi, Multiobjective Genetic Fuzzy Rule Selection of Single Granularity-Based Fuzzy Classification Rules and its Interaction with the Lateral Tuning of Membership Functions. Soft Computing 15:12 (2011) 2303-2318, doi: 10.1007/s00500-010-0671-2 . iconPdf.png

Bolita[1418] K. Trawinski, O. Cordón, A. Quirin, On designing fuzzy multiclassifier systems by combining FURIA with bagging and feature selection. International Journal of Uncertainty, Fuzziness, and Knowledge-based Systems 19:4 (2011) 589–633, doi: 10.1142/S0218488511007155 . iconPdf.png

Bolita[1470] D. Torres-Salinas, J G Moreno-Torres, N. Robinson-García, E. Delgado-López-Cózar, F. Herrera, Rankings ISI de las universidades españolas según campos y disciplinas científicas (2ª ed. 2011). El Profesional de la Información 20:6 (2011) 701-711. iconPdf.png

Bolita[1402] J. Alcalá-Fdez, R. Alcalá, F. Herrera, A Fuzzy Association Rule-Based Classification Model for High-Dimensional Problems with Genetic Rule Selection and Lateral Tuning. IEEE Transactions on Fuzzy Systems 19:5 (2011) 857-872 doi: 10.1109/TFUZZ.2011.2147794. iconPdf.png

Bolita[1373] J. Sanz, A. Fernandez, H. Bustince, F. Herrera, A Genetic Tuning to Improve the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of Ignorance and Lateral Position 52:6 (2011) 751-766. International Journal of Approximate Reasoning, doi:10.1016/j.ijar.2011.01.011. iconPdf.png

Bolita[1371] M. Galar, A. Fernandez, E. Barrenechea, H. Bustince, F. Herrera, An Overview of Ensemble Methods for Binary Classifiers in Multi-class Problems: Experimental Study on One-vs-One and One-vs-All Schemes. Pattern Recognition 44:8 (2011) 1761-1776, doi: 10.1016/j.patcog.2011.01.017. COMPLEMENTARY MATERIAL to the paper here: dataset partitions, results, figures, etc.. iconPdf.png

Bolita[1380] R. Alcalá, M.J. Gacto, F. Herrera, A Fast and Scalable Multi-Objective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression Problems. IEEE Transactions on Fuzzy Systems doi: 10.1109/TFUZZ.2011.2131657 19:4 (2011) 666-681. COMPLEMENTARY MATERIAL to the paper here: dataset partitions, results, figures, etc.. iconPdf.png

Bolita[1412] D. Torres-Salinas, J G Moreno-Torres, E. Delgado-López-Cózar, F. Herrera, A methodology for Institution-Field ranking based on a bidimensional analysis: the IFQ2A index. Scientometrics 88:3 (2011) 771-786. iconPdf.png

Bolita[1383] M.J. Gacto, R. Alcalá, F. Herrera, Interpretability of Linguistic Fuzzy Rule-Based Systems: An Overview of Interpretability Measures. Information Sciences, 181:20 (2011) 4340–4360 doi: 10.1016/j.ins.2011.02.021 COMPLEMENTARY MATERIAL to the paper here: links to the papers with doi, new contributions, etc.. iconPdf.png

Bolita[1327] I. Triguero, S. García, F. Herrera, Differential Evolution for Optimizing the Positioning of Prototypes in Nearest Neighbor Classification. Pattern Recognition 44 (4) (2011) 901-916, doi: 10.1016/j.patcog.2010.10.020. iconPdf.png

Bolita[1342] S. García, J. Derrac, J. Luengo, C.J. Carmona, F. Herrera, Evolutionary Selection of Hyperrectangles in Nested Generalized Exemplar Learning. Applied Soft Computing 11:3 (2011) 3032-3045. doi:10.1016/j.asoc.2010.11.030 . iconPdf.png

Bolita[1279] J.L. Aznarte M., J. Alcalá-Fdez, A. Arauzo, J.M. Benítez, Fuzzy autoregressive rules: Towards linguistic time series modeling. Econometric Reviews 30:6 (2011) 609–631, doi: 10.1080/07474938.2011.553569. iconPdf.png

Bolita[1277] J. Alcalá-Fdez, A. Fernandez, J. Luengo, J. Derrac, S. García, L. Sánchez, F. Herrera, KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework. Journal of Multiple-Valued Logic and Soft Computing 17:2-3 (2011) 255-287. SOFTWARE associated to the paper here. iconPdf.png

Bolita[1404] O. Cordón, A Historical Review of Evolutionary Learning Methods for Mamdani-type Fuzzy Rule-based Systems: Designing Interpretable Genetic Fuzzy Systems. International Journal of Approximate Reasoning 52:6 (2011) 894–913, doi: 10.1016/j.ijar.2011.03.004. iconPdf.png

Bolita[1368] D. Torres-Salinas, E. Delgado-López-Cózar, J G Moreno-Torres, F. Herrera, Rankings ISI de las universidades españolas según campos científicos: Descripción y resultados. El Profesional de la Información 20:1 (2011) 111-122. iconPdf.png

Bolita[1324] F. Herrera, C.J. Carmona, P. González and M.J. del Jesus, An overview on Subgroup Discovery: Foundations and Applications . Knowledge and Information Systems 29:3 (2011) 495-525, doi: 10.1007/s10115-010-0356-2. iconPdf.png

Bolita[1374] J. Derrac, S. García, D. Molina, F. Herrera, A Practical Tutorial on the Use of Nonparametric Statistical Tests as a Methodology for Comparing Evolutionary and Swarm Intelligence Algorithms. Swarm and Evolutionary Computation 1:1 (2011) 3-18, doi: 10.1016/j.swevo.2011.02.002. COMPLEMENTARY MATERIAL to the paper here: Software and tests description. iconPdf.png

Bolita[1276] J. Luengo, A. Fernandez, S. García, F. Herrera, Addressing Data Complexity for Imbalanced Data Sets: Analysis of SMOTE-based Oversampling and Evolutionary Undersampling. Soft Computing, 15 (10) (2011) 1909-1936 doi:10.1007/s00500-010-0625-8. iconPdf.png

Bolita Year 2010 (19):

Bolita[1316] I. Triguero, S. García, F. Herrera, IPADE: Iterative Prototype Adjustment for Nearest Neighbor Classification. IEEE Transactions on Neural Networks 21 (12) (2010) 1984-1990, doi: 10.1109/TNN.2010.2087415. COMPLEMENTARY MATERIAL to the paper here: datasets, experimental results and source codes. iconPdf.png

Bolita[1273] A. Fernandez, M. Calderón, E. Barrenechea, H. Bustince, F. Herrera, Solving Multi-Class Problems with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning and Preference Relations. Fuzzy Sets and Systems 161:23 (2010) 3064-3080, doi: 10.1016/j.fss.2010.05.016. iconPdf.png

Bolita[1104] A. Fernandez, S. García, J. Luengo, E. Bernadó-Mansilla, F. Herrera, Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy and Comparative Study. IEEE Transactions on Evolutionary Computation 14:6 (2010) 913-941 doi:10.1109/TEVC.2009.2039140. COMPLEMENTARY MATERIAL to the paper here: dataset partitions, results, figures, etc.. iconPdf.png

Bolita[1293] C. Carmona, P. González, M.J. del Jesus, F. Herrera, NMEEF-SD: Non-dominated Multi-objective Evolutionary algorithm for Extracting Fuzzy rules in Subgroup Discovery. IEEE Transactions on Fuzzy Systems Issue 18:5 (2010) 958-970 doi: 10.1109/TFUZZ.2010.2060200. iconPdf.png

Bolita[1278] J.A. Sanz, A. Fernandez, H. Bustince, F. Herrera, Improving the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets and Genetic Amplitude Tuning. Information Sciences 180:19 (2010) 3674-3685, doi: 10.1016/j.ins.2010.06.018. iconPdf.png

Bolita[1285] J. Derrac, S. García, F. Herrera, Stratified Prototype Selection based on a Steady-State Memetic Algorithm: A Study of scalability. Memetic Computing 2:3 (2010) 183-199, doi:10.1007/s12293-010-0048-1. iconPdf.png

Bolita[1242] A. Puris, R. Bello and F. Herrera, Analysis of the efficacy of a Two-Stage methodology for Ant Colony Optimization: Case of study with TSP and QAP. Expert Systems with Applications 37:7 (2010) 5443-5453, doi: 10.1016/j.eswa.2010.02.069. iconPdf.png

Bolita[1228] M.J. Gacto, R. Alcalá, F. Herrera, Integration of an Index to Preserve the Semantic Interpretability in the Multi-Objective Evolutionary Rule Selection and Tuning of Linguistic Fuzzy Systems. IEEE Transactions on Fuzzy Systems 18:3 (2010) 515-531, doi: 10.1109/TFUZZ.2010.2041008. iconPdf.png

Bolita[1227] A. Fernandez, M.J. del Jesus, F. Herrera, On the 2-Tuples Based Genetic Tuning Performance for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets. Information Sciences 180:8 (2010) 1268-1291, doi:10.1016/j.ins.2009.12.014. COMPLEMENTARY MATERIAL to the paper here: dataset partitions, results, figures, etc.. iconPdf.png

Bolita[1229] F.J. Berlanga, A.J. Rivera, M.J. del Jesus, F. Herrera, GP-COACH: Genetic Programming based learning of COmpact and ACcurate fuzzy rule based classification systems for high dimensional problems. Information Sciences 180:8 (2010) 1183-1200, doi: 10.1016/j.ins.2009.12.020. iconPdf.png

Bolita[1071] M. Mucientes, J. Alcalá-Fdez, R. Alcalá, J. Casillas, A case study for learning behaviors in mobile robotics by evolutionary fuzzy systems. Expert Systems With Applications 37:2 (2010) 1471–1493, doi: 10.1016/j.eswa.2009.06.095. iconPdf.png

Bolita[1092] P. Espejo, S. Ventura, F. Herrera, A Survey on the Application of Genetic Programming to Classification. IEEE Transactions on Systems, Man, and Cybernetics--Part C: Applications and Reviews 40:2 (2010) 121-144, doi:10.1109/TSMCC.2009.2033566 . iconPdf.png

Bolita[1100] J. Derrac, S. García, F. Herrera, A Survey on Evolutionary Instance Selection and Generation. International Journal of Applied Metaheuristic Computing 1:1 (2010) 60-92, doi:10.4018/IJAMC.2010010104. iconPdf.png

Bolita[1206] S. García, A. Fernandez, J. Luengo, F. Herrera, Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental Analysis of Power. Information Sciences 180 (2010) 2044–2064. doi: 10.1016/j.ins.2009.12.010. COMPLEMENTARY MATERIAL to the paper here: Software and tests description . iconPdf.png

Bolita[1112] J. Luengo, S. García, F. Herrera, A Study on the Use of Imputation Methods for Experimentation with Radial Basis Function Network Classifiers Handling Missing Attribute Values: The good synergy between RBFs and EventCovering method. Neural Networks 23 406-418, doi:10.1016/j.neunet.2009.11.014. COMPLEMENTARY MATERIAL to the paper here: dataset partitions, results, figures, etc.. iconPdf.png

Bolita[0759] O. Cordón, A. Quirin, Comparing Two Genetic Overproduce-and-choose Strategies for Fuzzy Rule-based Multiclassification Systems Generated by Bagging and Mutual Information-based Feature Selection. International Journal of Hybrid and Intelligent Systems 7:1 (2010) 45-64. iconPdf.png

Bolita[1226] J. Derrac, S. García, F. Herrera, IFS-CoCo: Instance and Feature Selection based on Cooperative Coevolution with Nearest Neighbor Rule. Pattern Recognition 43:6 (2010) 2082-2105. doi: 10.1016/j.patcog.2009.12.012 . iconPdf.png

Bolita[1186] J. Alcalá-Fdez, N. Flugy-Pape, A. Bonarini, F. Herrera, Analysis of the Effectiveness of the Genetic Algorithms based on Extraction of Association Rules. Fundamenta Informaticae 98:1 (2010) 1-14. iconPdf.png

Bolita[1043] J. Luengo, F. Herrera, Domains of Competence of Fuzzy Rule Based Classification Systems with Data Complexity measures: A case of study using a Fuzzy Hybrid Genetic Based Machine Learning Method. Fuzzy Sets and Systems, 161 (1) (2010) 3-19 doi:10.1016/j.fss.2009.04.001 . iconPdf.png

Bolita Year 2009 (21):

Bolita[0875] S. García, J.R. Cano, E. Bernadó-Mansilla, F. Herrera, Diagnose of Effective Evolutionary Prototype Selection using an Overlapping Measure. International Journal of Pattern Recognition and Artificial Intelligence 23:8 (2009) 1527-1548. iconPdf.png

Bolita[1054] R. Alcalá, P. Ducange, F. Herrera, B. Lazzerini, F. Marcelloni, A Multi-Objective Evolutionary Approach to Concurrently Learn Rule and Data Bases of Linguistic Fuzzy Rule-Based Systems. IEEE Transactions on Fuzzy Systems 17:5 (2009) 1106-1122, doi: 10.1109/TFUZZ.2009.2023113. iconPdf.png

Bolita[0828] F.J. Martínez-López, J. Casillas, Marketing intelligent systems for consumer behaviour modelling by a descriptive induction approach based on genetic fuzzy systems. Industrial Marketing Management 38:7 (2009) 714-731, doi: 10.1016/j.indmarman.2008.02.003. iconPdf.png

Bolita[1088] L. Sánchez, I. Couso, J. Casillas, Genetic learning of fuzzy rules based on low quality data. Fuzzy Sets and Systems 160:17 (2009) 2524-2552 doi: 10.1016/j.fss.2009.03.004. iconPdf.png

Bolita[1047] S. García, A. Fernandez, F. Herrera, Enhancing the Effectiveness and Interpretability of Decision Tree and Rule Induction Classifiers with Evolutionary Training Set Selection over Imbalanced Problems. Applied Soft Computing 9 (2009) 1304-1314, doi:10.1016/j.asoc.2009.04.004. iconPdf.png

Bolita[0898] S. García, A. Fernandez, J. Luengo, F. Herrera, A Study of Statistical Techniques and Performance Measures for Genetics-Based Machine Learning: Accuracy and Interpretability. Soft Computing 13:10 (2009) 959-977, doi:10.1007/s00500-008-0392-y. COMPLEMENTARY MATERIAL to the paper here: Software and tests description. iconPdf.png

Bolita[1018] A. Fernandez, F. Herrera, M.J. del Jesus, On the Influence of an Adaptive Inference System in Fuzzy Rule Based Classification Systems for Imbalanced Data-Sets. Expert Systems With Applications 36:6 (2009) 9805-9812, doi: 10.1016/j.eswa.2009.02.048. iconPdf.png

Bolita[0826] S. García, F. Herrera, Evolutionary Under-Sampling for Classification with Imbalanced Data Sets: Proposals and Taxonomy. Evolutionary Computation 17:3 (2009) 275-306. iconPdf.png

Bolita[0671] R. Alcalá, J. Alcalá-Fdez, M.J. Gacto, F. Herrera, Improving Fuzzy Logic Controllers Obtained by Experts: A Case Study in HVAC Systems. Applied Intelligence 31:1 (2009) 15-30, doi:10.1007/s10489-007-0107-6. iconPdf.png

Bolita[0829] J. Casillas, F.J. Martínez-López, A knowledge discovery method based on genetic fuzzy systems for obtaining consumer behaviour patterns. An empirical application to a web-based trust model. International Journal of Management and Decision Making 10:5-6 (2009) 402-428 doi: 10.1504/IJMDM.2009.026685. iconPdf.png

Bolita[1052] A. Orriols-Puig, J. Casillas, F.J. Martínez-López, Unsupervised learning of fuzzy association rules for consumer behavior modeling. Mathware & Soft Computing 16:1 (2009) 29-43. iconPdf.png

Bolita[0896] A. Fernandez, M.J. del Jesus, F. Herrera, Hierarchical Fuzzy Rule Based Classification Systems with Genetic Rule Selection for Imbalanced Data-Sets. International Journal of Approximate Reasoning 50 (2009) 561-577, doi: 10.1016/j.ijar.2008.11.004. COMPLEMENTARY MATERIAL to the paper here: dataset partitions, results, figures, etc.. iconPdf.png

Bolita[0837] M.J. Gacto, R. Alcalá, F. Herrera, Adaptation and Application of Multi-Objective Evolutionary Algorithms for Rule Reduction and Parameter Tuning of Fuzzy Rule-Based Systems. Soft Computing 13:5 (2009) 419-436, doi:10.1007/s00500-008-0359-z. iconPdf.png

Bolita[0839] A. Orriols-Puig, J. Casillas, E. Bernadó-Mansilla, Fuzzy-UCS: a Michigan-style learning fuzzy-classifier system for supervised learning. IEEE Transactions on Evolutionary Computation 13:2 (2009) 260-283 doi: 10.1109/TEVC.2008.925144. iconPdf.png

Bolita[0893] J. Luengo, S. García, F. Herrera, A Study on the Use of Statistical Tests for Experimentation with Neural Networks: Analysis of Parametric Test Conditions and Non-Parametric Tests. Expert Systems with Applications 36 (2009) 7798-7808 doi:10.1016/j.eswa.2008.11.041 . COMPLEMENTARY MATERIAL to the paper here: Software and tests description. iconPdf.png

Bolita[0758] J. Alcalá-Fdez, L. Sánchez, S. García, M.J. del Jesus, S. Ventura, J.M. Garrell, J. Otero, C. Romero, J. Bacardit, V.M. Rivas, J.C. Fernández, F. Herrera, KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems. Soft Computing 13:3 (2009) 307-318 doi: 10.1007/s00500-008-0323-y. SOFTWARE associated to the paper here. iconPdf.png

Bolita[0650] M. Mucientes, R. Alcalá, J. Alcalá-Fdez, J. Casillas, Learning Weighted Linguistic Rules to Control an Autonomous Robot. International Journal of Intelligent Systems 24:3 (2009) 226–251 doi: 10.1002/int.20334. iconPdf.png

Bolita[0769] C. Romero, P. González, S. Ventura, M.J. del Jesus, F. Herrera, Evolutionary algorithms for subgroup discovery in e-learning: A practical application using Moodle data. Expert Systems With Applications 36 (2009) 1632-1644, doi:10.1016/j.eswa.2007.11.026. iconPdf.png

Bolita[0771] J. Casillas, F.J. Martínez-López, Mining Uncertain Data with Multiobjective Genetic Fuzzy Systems to Be Applied in Consumer Behaviour Modelling. Expert Systems with Applications 36:2 (2009) 1645-1659, doi: doi:10.1016/j.eswa.2007.11.035. iconPdf.png

Bolita[0838] J. Alcalá-Fdez, R. Alcalá, M.J. Gacto, F. Herrera, Learning the Membership Function Contexts for Mining Fuzzy Association Rules by Using Genetic Algorithms. Fuzzy Sets and Systems 160:7 (2009) 905-921 doi:10.1016/j.fss.2008.05.012 . iconPdf.png

Bolita[0840] J. Casillas, P. Martínez, A.D. Benítez, Learning consistent, complete and compact sets of fuzzy rules in conjunctive normal form for regression problems. Soft Computing 13:5 (2009) 451-465, doi: 10.1007/s00500-008-0361-5. iconPdf.png

Bolita Year 2008 (10):

Bolita[0882] S. García, F. Herrera, An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons. Journal of Machine Learning Research 9 (2008) 2677-2694. COMPLEMENTARY MATERIAL to the paper here: Software and tests description. iconPdf.png

Bolita[0878] A. Orriols-Puig, J. Casillas, E. Bernadó-Mansilla, Genetic-based machine learning systems are competitive for pattern recognition. Evolutionary Intelligence 1:3 (2008) 209-232, doi: 10.1007/s12065-008-0013-9. iconPdf.png

Bolita[0847] J.R. Cano, S. García, F. Herrera, Subgroup Discovery in Large Size Data Sets Preprocessed Using Stratified Instance Selection for Increasing the Presence of Minority Classes. Pattern Recognition Letters 29 (2008) 2156-2164, doi:10.1016/j.patrec.2008.08.001. iconPdf.png

Bolita[0772] A. Fernandez, S. García, M.J. del Jesus, F. Herrera, A Study of the Behaviour of Linguistic Fuzzy Rule Based Classification Systems in the Framework of Imbalanced Data Sets. Fuzzy Sets and Systems, 159:18 (2008) 2378-2398, doi: 10.1016/j.fss.2007.12.023. iconPdf.png

Bolita[0827] S. García, J.R. Cano, F. Herrera, A Memetic Algorithm for Evolutionary Prototype Selection: A Scaling Up Approach. Pattern Recognition 41:8 (2008) 2693-2709, doi:10.1016/j.patcog.2008.02.006. iconPdf.png

Bolita[0721] J.R. Cano, F. Herrera, M. Lozano, S. García, Making CN2-SD Subgroup Discovery Algorithm scalable to Large Size Data Sets using Instance Selection. Expert Systems with Applications 35 (2008) 1949-1965, doi:10.1016/j.eswa.2007.08.083. iconPdf.png

Bolita[0685] J. Otero, L. Sánchez, J. Alcalá-Fdez, Fuzzy-genetic optimization of the parameters of a low cost system for the optical measurement of several dimensions of vehicles. Soft Computing 12:8 (2008) 751–764, doi: 10.1007/s00500-007-0234-3. iconPdf.png

Bolita[0824] A. Araúzo, J.M. Benítez, J.L. Castro, Consistency measures for feature selection. Journal of Intelligent Information Systems 30:3 (2008) 273-292, doi:10.1007/s10844-007-0037-0. iconPdf.png

Bolita[0618] R. Muñoz-Salinas, E. Aguirre, O. Cordón, M. Garcia-Silvente, Automatic Tuning of a Fuzzy Visual System Using Evolutionary Algorithms: Single-objective vs. Multiobjective Approaches. IEEE Transactions on Fuzzy Systems 16:2 (2008) 485-501, doi: 10.1109/TFUZZ.2006.889954. iconPdf.png

Bolita[0760] F. Herrera, Genetic Fuzzy Systems: Taxonomy, Current Research Trends and Prospects. Evolutionary Intelligence 1 (2008) 27-46, doi: 10.1007/s12065-007-0001-5. iconPdf.png

Bolita Year 2007 (14):

Bolita[0767] J. Acosta, A. Nebot, P. Villar, J.M. Fuertes, Learning fuzzy partitions in FIR methodology. International Journal of General Systems 36:6 (2007) 703-731, doi: 10.1080/03081070701458548. iconPdf.png

Bolita[0654] F.A. Márquez, A. Peregrín and F. Herrera, Cooperative Evolutionary Learning of Fuzzy Rules and Parametric Aggregation Connectors for Mamdani Linguistic Fuzzy Systems. IEEE Transactions on Fuzzy Systems, 15:6 (2007) 1162-1178, doi: 10.1109/TFUZZ.2007.904121. iconPdf.png

Bolita[0753] J. Acosta, A. Nebot, P. Villar, J.M. Fuertes, Optimization of Fuzzy Partitions for Inductive Reasoning using Genetic Algorithms. International Journal of Systems Science 38:12 (2007) 991-1011, doi: 10.1080/00207720701657581. iconPdf.png

Bolita[0651] R. Alcalá, M.J. Gacto, F. Herrera, J. Alcalá-Fdez, A Multi-objective Genetic Algorithm for Tuning and Rule Selection to Obtain Accurate and Compact Linguistic Fuzzy Rule-Based Systems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 15:5 (2007) 539–557, doi:10.1142/S0218488507004868 . iconPdf.png

Bolita[0344] R. Alcalá, J. Alcalá-Fdez, J. Casillas, O. Cordón, F. Herrera, Local Identification of Prototypes for Genetic Learning of Accurate TSK Fuzzy Rule-Based Systems. International Journal of Intelligent Systems 22:9 (2007) 909-941, doi:10.1002/int.20232. iconPdf.png

Bolita[0825] J. Casillas, F.J. Martínez-López, Knowledge Discovery by Genetic Fuzzy Systems Applied to Consumer Behavior Modelling. Romanian Marketing Review 3 (2007) 111-142. iconPdf.png

Bolita[0564] M. Mucientes, J. Casillas, Quick design of fuzzy controllers with good interpretability in mobile robotics. IEEE Transactions on Fuzzy Systems 15:4 (2007) 636-651, doi:10.1109/TFUZZ.2006.889889. iconPdf.png

Bolita[0589] M.J. del Jesus, P. González, F. Herrera, M. Mesonero, Evolutionary Fuzzy Rule Induction Process for Subgroup Discovery: A Case Study in Marketing. IEEE Transactions on Fuzzy Systems 15:4 (2007) 578-592, doi:10.1109/TFUZZ.2006.890662. iconPdf.png

Bolita[0598] R. Alcalá, J. Alcalá-Fdez, F. Herrera, A Proposal for the Genetic Lateral Tuning of Linguistic Fuzzy Systems and its Interaction with Rule Selection. IEEE Transactions on Fuzzy Systems 15:4 (2007) 616-635, doi:10.1109/TFUZZ.2006.889880. iconPdf.png

Bolita[0952] F. Araque, R.A. Carrasco, A. Salguero, L. Martínez, M.A. Vila, Fuzzy extended dependencies to support decision-making in project management. Journal of Multiple-Valued Logic and Soft Computing 14 (2008) 435-455. iconPdf.png

Bolita[0543] J.R. Cano, F. Herrera, M. Lozano, Evolutionary Stratified Training Set Selection for Extracting Classification Rules with Trade-off Precision-Interpretability. Data and Knowledge Engineering 60 (2007) 90-108, doi:10.1016/j.datak.2006.01.008. iconPdf.png

Bolita[0556] R. Alcalá, J. Alcalá-Fdez, M.J. Gacto, F. Herrera, Rule Base Reduction and Genetic Tuning of Fuzzy Systems based on the Linguistic 3-Tuples Representation. Soft Computing 11:5 (2007) 401-419, doi:10.1007/s00500-006-0106-2. iconPdf.png

Bolita[0572] R. Alcalá, J. Alcalá-Fdez, F. Herrera, J. Otero, Genetic Learning of Accurate and Compact Fuzzy Rule Based Systems Based on the 2-Tuples Linguistic Representation. International Journal of Approximate Reasoning 44:1 (2007) 45-64, doi:10.1016/j.ijar.2006.02.007. iconPdf.png

Bolita[0346] J. Alcalá-Fdez, F. Herrera, F. Márquez, A. Peregrín, Increasing Fuzzy Rules Cooperation Based on Evolutionary Adaptive Inference Systems. International Journal of Intelligent Systems 22:9 (2007) 1035-1064, doi:10.1002/int.20237. iconPdf.png

Bolita Year 2006 (2):

Bolita[0434] J.R. Cano, F. Herrera, M. Lozano, On the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining. Applied Soft Computing 6 (2006) 323-332, doi: 10.1016/j.asoc.2005.02.006. iconPdf.png

Bolita[0343] R. Alcalá, J. Alcalá-Fdez, J. Casillas, O. Cordón, F. Herrera, Hybrid learning models to get the interpretability-accuracy trade-off in Fuzzy Modelling. Soft Computing 10:9 (2006) 717-734, doi: 10.1007/s00500-005-0002-1. iconPdf.png

Bolita Year 2005 (5):

Bolita[0340] R. Alcalá, J. Casillas, O. Cordón, A. González, F. Herrera, A Genetic Rule Weighting and Selection Process for Fuzzy Control of Heating, Ventilating and Air Conditioning Systems. Engineering Applications of Artificial Intelligence 18:3 (2005) 279-296, doi: 10.1016/j.engappai.2004.09.007. iconPdf.png

Bolita[0347] J. Casillas, O. Cordón, I. Fernández de Viana, F. Herrera, Learning Cooperative Linguistic Fuzzy Rules Using the Best-Worst Ant Systems Algorithm. International Journal of Intelligent Systems 20 (2005) 433-452, doi: 10.1002/int.20074. iconPdf.png

Bolita[0339] J. Casillas, O. Cordón, M.J. del Jesús, F. Herrera, Genetic Tuning of Fuzzy Rule Deep Structures Preserving Interpretability and Its Interaction With Fuzzy Rule Set Reduction. IEEE Trans. on Fuzzy Systems 13:1 (2005) 13-29, doi: 10.1109/TFUZZ.2004.839670. iconPdf.png

Bolita[0401] J.R. Cano, F. Herrera, M. Lozano, Stratification for Scaling Up Evolutionary Prototype Selection. Pattern Recognition Letters, 26, (2005), 953-963, doi: 10.1016/j.patrec.2004.09.043 . iconPdf.png

Bolita[0504] F. Herrera, Genetic Fuzzy Systems: Status, Critical Considerations and Future Directions. International Journal of Computational Intelligence Research (IJCIR) 1:1 (2005) 59-67. iconPdf.png

Bolita Year 2004 (4):

Bolita[0951] J. Galindo, A. Urrutia, R.A. Carrasco, M. Piattini, Relaxing Constraints in Enhanced Entity-Relationship Models Using Fuzzy Quantifiers. IEEE Transactions on Fuzzy Systems 12:6 (2004) 780-796, doi: 10.1109/TFUZZ.2004.836088. iconPdf.png

Bolita[0331] O. Cordón, F. Gomide, F. Herrera, F. Hoffmann, L. Magdalena, Ten Years of Genetic Fuzzy Systems: Current Framework and New Trends. Fuzzy Sets and Systems 141:1 (2004) 5-31, doi: 10.1016/S0165-0114(03)00111-8. iconPdf.png

Bolita[0454] J. Casillas, F.J. Martínez-López, F.J. Martínez, Fuzzy association rules for estimating consumer behaviour models and their application to explaining trust in Internet shopping. Fuzzy Economic Review IX:2 (2004) 3-26.

Bolita[0332] O. Cordón, F. Herrera, F.A. Márquez, A. Peregrin, A Study on the Evolutionary Adaptive Defuzzification Methods in Fuzzy Modelling. International Journal of Hybrid Intelligent Systems 1:1 (2004) 36-48.

Bolita Year 2003 (4):

Bolita[0361] J.R. Cano, F. Herrera, M. Lozano, Using Evolutionary Algorithms as Instance Selection for Data Reduction in KDD: An Experimental Study. IEEE Trans. on Evolutionary Computation 7:6 (2003) 561-575, doi: 10.1109/TEVC.2003.819265. iconPdf.png

Bolita[0011] R. Alcalá, J.R. Cano, O. Cordón, F. Herrera, P. Villar, I. Zwir, Linguistic Modeling with Hierarchical Systems of Weighted Linguistic Rules. International Journal of Approximate Reasoning 32:2-3 (2003) 187-215, doi: 10.1016/S0888-613X(02)00083-X. iconPdf.png

Bolita[0013] R. Alcalá, J. Casillas, O. Cordón, F. Herrera, Linguistic Modeling with Weighted Double-Consequent Fuzzy Rules Based on Cooperative Coevolutionary Learning. Integrated Computer Aided Engineering 10 (4) (2003) 343-355. iconPdf.png

Bolita[0015] O. Cordón, F. Herrera, I. Zwir, A Hierarchical Knowledge-Based Environment for Linguistic Modeling: Models and Iterative Methodology. Fuzzy Sets and Systems 138:2 (2003) 307-341. iconPdf.png

Bolita Year 2002 (5):

Bolita[0023] J. Casillas, O. Cordón, F. Herrera, COR: A Methodology to Improve Ad Hoc Data-Driven Linguistic Rule Learning Methods by Inducing Cooperation Among Rules. IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics 32:4 (2002) 526-537, doi: 10.1109/TSMCB.2002.1018771. iconPdf.png

Bolita[0178] J.R. Cano, O. Cordón, F. Herrera, L. Sánchez, A Greedy Randomized Adaptive Search Procedure Applied to the Clustering Problem as an Initialization Process Using K-Means as a Local Search Procedure. International Journal of Intelligent and Fuzzy Systems 12 (2002) 235-242. iconPdf.png

Bolita[0022] L. Sánchez, J. Casillas, O. Cordón, M.J. Del Jesus, Some Relationships Between Fuzzy and Random Set-Based Classifiers and models. International Journal of Approximate Reasoning 29:2 (2002) 175-213, doi: 10.1016/S0888-613X(01)00063-9. iconPdf.png

Bolita[0025] O. Cordón, F. Herrera, I. Zwir, Linguistic Modeling by Hierarchical Systems of Linguistic Rules. IEEE Transactions on Fuzzy Systems 10:1 (2002) 2-20, doi: 10.1109/91.983275. iconPdf.png

Bolita[0821] J.L. Castro, C.J. Mantas, J.M. Benítez, Interpretation of Artificial Neural Networks by means of Fuzzy Rules. IEEE Transactions on Neural Networks 13:1 (2002) 101-116, doi:10.1109/72.977279. iconPdf.png

Bolita Year 2001 (8):

Bolita[0039] O. Cordón, F. Herrera, I. Zwir, Fuzzy Modeling by Hierarchically Built Fuzzy Rule Bases. International Journal of Approximate Reasoning 27 (2001) 61-93. iconPdf.png

Bolita[0043] O. Cordón, F. Herrera, Hybridizing Genetic Algorithms with Sharing Scheme and Evolution Strategies for Designing Approximate Fuzzy Rule-Based Systems. Fuzzy Sets and Systems 118:2 (2001) 235-255. iconPdf.png

Bolita[0017] R. Alcalá, J. Casillas, O. Cordón, F. Herrera, Building Fuzzy Graphs: Features and Taxonomy of Learning Non-Grid-Oriented Fuzzy Rule-Based Systems. International Journal of Intelligent Fuzzy Systems, 11 (2001) 99-119. iconPdf.png

Bolita[0035] R. Alcalá, J. Casillas, O. Cordón, F. Herrera, Improvement to the Cooperative Rules Methodology by Using the Ant Colony System Algorithm. Mathware and Soft Computing Vol 8:3 (2001) 321-335. iconPdf.png

Bolita[0019] R. Alcalá, J. Casillas, J.L. Castro, A. Gonzalez, F. Herrera, A Multicriteria Genetic Tuning for Fuzzy Logic Controllers. Mathware and Soft Computing, Vol. 8:2 (2001) 179-201. iconPdf.png

Bolita[0021] O. Cordón, F. Herrera, P. Villar, Generating the Knowledge Base of a Fuzzy Rule-Based System by the Genetic Learning of Data Base. IEEE Transactions on Fuzzy Systems 9:4 (2001) 667-674. iconPdf.png

Bolita[0032] J. Casillas, O. Cordón, F. Herrera, M.J. Del Jesus, Genetic Feature Selection in a Fuzzy Rule-Based Classification System Learning Process for High-Dimensional Problems. Information Sciences 136:1-4 (2001) 135-157. iconPdf.png

Bolita[0036] O. Cordón, F. Herrera, L. Magdalena, P. Villar, A Genetic Learning Process for the Scaling Factors, Granularity and Contexts of the Fuzzy Rule-Based System Data Base. Information Science 136 (2001) 85-107. iconPdf.png

Bolita Year 2000 (4):

Bolita[0820] J.L. Castro, C.J. Mantas, J.M. Benítez, Neural Networks with a Continuous Increasing Squashing function in the output are Universal Approximators. Neural Networks 13:6 (2000) 561-563, doi:10.1016/S0893-6080(00)00031-9. iconPdf.png

Bolita[0049] O. Cordón, F. Herrera, P. Villar, Analysis and Guidelines to Obtain a Good Fuzzy Partition Granularity for Fuzzy Rule-Based Systems using Simulated Annealing. International Journal of Approximate Reasoning 25:3 (2000) 187-215. iconPdf.png

Bolita[0050] O. Cordón, F. Herrera, A Proposal for Improving the Accuracy of Linguistic Modeling. IEEE Transactions on Fuzzy Systems 8:3 (2000) 335-344. iconPdf.png

Bolita[0054] O. Cordón, F. Herrera, A. Peregrín, Searching for Basic Properties Obtaining Robust Implication Operators in Fuzzy Control. Fuzzy Sets and Systems 111:2 (2000) 237-251. iconPdf.png

Bolita Year 1999 (5):

Bolita[0056] O. Cordón, F. Herrera, A Two-Stage Evolutionary Process for Designing TSK Fuzzy Rule-Based Systems. IEEE Transactions on Systems, Man,and Cybernetics. Part B: Cybernetics Vol. 29:6 (December 1999) 703-715. iconPdf.png

Bolita[0057] O. Cordón, F. Herrera, A. Peregrín, A Practical Study on the Implementation of Fuzzy Logic Controllers. The International Journal of Intelligent Control and Systems 3 (1999) 49-91. iconPdf.png

Bolita[0059] O. Cordón, M. J. del Jesus, F. Herrera, M. Lozano, MOGUL: A Methodology to Obtain Genetic fuzzy rule-based systems Under the iterative rule Learning approach. International Journal of Intelligent Systems Vol. 14:11 (1999) 1123-1153. iconPdf.png

Bolita[0061] O. Cordón, M.J. del Jesus, F. Herrera, A Proposal on Reasoning Methods in Fuzzy Rule-Based Classification Systems. International Journal of Approximate Reasoning Vol. 20 (1999), 21-45. iconPdf.png

Bolita[0062] O. Cordón, F. Herrera, L. Sánchez, Solving Electrical Distribution Problems Using Hybrid Evolutionary Data Analysis Techniques. Applied Intelligence 10 (1999) 5-24. iconPdf.png

Bolita Year 1998 (5):

Bolita[0064] O. Cordón, M.J. del Jesus, F. Herrera, Genetic Learning of Fuzzy Rule-Based Classification Systems Cooperating with Fuzzy Reasoning Methods. International Journal of Intelligent Systems 13:10-11 (1998) 1025-1053. iconPdf.png

Bolita[0065] F. Herrera, M. Lozano, J.L. Verdegay, A Learning Process for Fuzzy Control Rules using Genetic Algorithms. Fuzzy Sets and Systems 100 (1998) 143-158. iconPdf.png

Bolita[0069] O. Cordón, M.J. del Jesus, F. Herrera, M. Lozano, Modelado Cualitativo Utilizando una Metodología Evolutiva de Aprendizaje Iterativo de Bases de Reglas Difusas. Revista Iberoamericana de la Asociación Española para la Inteligencia Artificial. Num. 5 (1998), 56-61. iconPdf.png

Bolita[0819] J.M. Benítez, A. Blanco, M. Delgado, I. Requena, New Aspects on Extraction of Fuzzy Rules using Neural Networks. Mathware & Soft Computing 5 (1998) 333-343. iconPdf.png

Bolita[0063] O. Cordón, M.J. del Jesus, F. Herrera, Analyzing the Reasoning Mechanisms in Fuzzy Rule-Based Classification Systems. Mathware and Soft Computing. Vol. 5: 2-3 (1998), 321-332. iconPdf.png

Bolita Year 1997 (5):

Bolita[0818] J.M. Benítez, J.L. Castro, I. Requena, Are Artificial Neural Networks Black Boxes?. IEEE Transactions on Neural Networks 8:5 (1997) 1156-1164, doi:10.1109/72.623216. iconPdf.png

Bolita[0072] O. Cordón, F. Herrera, A Three-Stage Evolutionary Process for Learning Descriptive and Approximative Fuzzy Logic Controller Knowledge Bases from Examples. International Journal of Approximate Reasoning 17:4 (1997) 369-407. iconPdf.png

Bolita[0073] A. Gonzalez, F. Herrera, Multi-Stage Genetic Fuzzy Systems Based on the Iterative Rule Learning Approach. Mathware and Soft Computing 4:3 (1997) 233-249. iconPdf.png

Bolita[0076] F. Herrera, L. Magdalena, Genetic Fuzzy Systems. Tatra Mountains Mathematical Publications Vol. 13, 1997, 93-121. R. Mesiar,B. Riecan(Eds.) Fuzzy Structures. Current Trends. L. N. Tutorial: Genetic Fuzzy Systems.7th IFSA World Congress,Prage,June 97.

Bolita[0079] O. Cordón, F. Herrera, A. Peregrín, Applicability of the Fuzzy Operators in the Design of Fuzzy Logic Controllers. Fuzzy Sets and Systems Vol. 86:1 (1997), 15-41. iconPdf.png

Bolita Year 1996 (2):

Bolita[0817] J.M. Benítez, A. Blanco, M. Delgado, I. Requena, Neural Methods for Obtaining Fuzzy Rules. Mathware & Soft Computing 3 (1996) 371-382. iconPdf.png

Bolita[0082] O. Cordón, F. Herrera, E. Herrera-Viedma, M. Lozano, Genetic Algorithms and Fuzzy Logic in Control Processes. Archives of Control Sciences. Vol. 5 (1996) 135-168. iconPdf.png

Bolita Year 1995 (3):

Bolita[0095] E. Cárdenas, J.C. Castillo, O. Cordón, F. Herrera, A. Peregrín, Applicability of T-Norms in Fuzzy Control. BUSEFAL 61 (1995) 28-36. iconPdf.png

Bolita[0088] F. Herrera, M. Lozano, J.L. Verdegay, The Use of Fuzzy Connectives to Design real-Coded Genetic Algorithms. Mathware and Soft Computing. Vo. 1:3 (1995) 239-251. iconPdf.png

Bolita[0092] F. Herrera, M. Lozano, J.L. Verdegay, Tuning Fuzzy Logic Controllers by Genetic Algorithms. International Journal of Approximate Reasoning 12 (1995) 299-315, doi: 10.1016/0888-613X(94)00033-Y. iconPdf.png

Bolita Year 1994 (1):

Bolita[0099] E. Cárdenas, J.C. Castillo, O. Cordón, F. Herrera, A. Peregrín, Influence of Fuzzy Implication Functions and Defuzzification Methods in Fuzzy Control. BUSEFAL 57 (1994) 69-79. iconPdf.png

 

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