Journal Contributions: Published

Jump to Year:
        2009  2008  2007  2006  2005  2004  2003  2002  2001  2000
        1998  1997  1994

2009
				bib
	Y. Nojima, H. Ishibuchi, I. Kuwajima. Parallel distributed genetic fuzzy rule selection. Soft Computing 13:5 (2009) 511-519			bib
2008
	J.-N. Choi, S.-K. Oh, W. Pedrycz. Structural and parametric design of fuzzy inference systems using hierarchical fair competition-based parallel genetic algorithms and information granulation. International Journal of Approximate Reasoning 49:3 (2008) 631-648			bib
	E.G. Mansoori, M.J. Zolghadri, S.D. Katebi. SGERD: A steady-state genetic algorithm for extracting fuzzy classification rules from data. IEEE Transactions on Fuzzy Systems 16:4 (2008) 1061-1071			bib
2007
				bib
	C.-H. Tsang, J.H. Tsai, H. Wang. Genetic-fuzzy rule mining approach and evaluation of feature selection techniques for anomaly intrusion detection. Pattern Recognition 40:9 (2007) 2373-2391			bib
2006
				bib
	N. Xiong, P. Funk. Construction of fuzzy knowledge bases incorporating feature selection. Soft Computing 10:9 (2006) 796-804			bib
2005
	J. Abonyi, B. Feil, A. Abraham. Computational intelligence in data mining. Informatica 29:1 (2005) 3-12			bib
				bib
	H. Wang, S. Kwong, Y. Jin, W. Wei, K.F. Man. Multi-objective hierarchical genetic algorithm for interpretable fuzzy rule-based knowledge extraction. Fuzzy Sets and Systems 149:1 (2005) 149-186			bib
2004
	H. Ishibuchi, T. Yamamoto. Comparison of heuristic criteria for fuzzy rule selection in classification problems. Fuzzy Optimization and Decision Making 3:2 (2004) 119-139			bib
	W. Pedrycz. Logic-driven fuzzy modeling with fuzzy multiplexers. Engineering Applications of Artificial Intelligence 17:4 (2004) 383-391			bib
2003
	J. Abonyi, J.A. Roubos, F. Szeifert. Data-driven generation of compact, accurate, and linguistically sound fuzzy classifiers based on a decision-tree initialization. International Journal of Approximate Reasoning 32:1 (2003) 1-21			bib
				bib
2002
				bib
	S. Yu, S. Backer, P. Scheunders. Genetic feature selection combined with composite fuzzy nearest neighbor classifiers for hyperspectral satellite imagery. Pattern Recognition Letters 23:1-3 (2002) 183-190			bib
2001
				bib
				bib
	H. Ishibuchi, T. Nakashima, T. Murata. Three-objective genetics-based machine learning for linguistic rule extraction. Information Sciences 136:1-4 (2001) 109-133			bib
	F. Kojima, N. Kubota, S. Hashimoto. Identification of crack profiles using genetic programming and fuzzy inference. Journal of Materials Processing Technology 108:2 (2001) 263-267			bib
2000
				bib
1998
				bib
				bib
	H. Ishibuchi, T. Murata, M. Gen. Performance evaluation of fuzzy rule-based classification systems obtained by multi-objective genetic algorithms. Computers and Industrial Engineering 35:3-4 (1998) 575-578			bib
1997
	H. Ishibuchi, T. Nakashima, T. Murata. Comparison of the Michigan and Pittsburgh approaches to the design of fuzzy classification systems. Electronics and Communications in Japan, Part III: Fundamental Electronic Science 80:12 (1997) 10-18			bib
1994
	H. Ishibuchi, K. Nozaki, N. Yamamoto, H. Tanaka. Construction of fuzzy classification systems with rectangular fuzzy rules using genetic algorithms. Fuzzy Sets and Systems 65:2-3 (1994) 237-253			bib

 Contributions to Books Chapters

Jump to Year:   2008  2007  2006

2008
				bib
2007
				bib
2006
	H. Ishibuchi, Y. Nojima. Fuzzy ensemble design through multi-objective fuzzy rule selection. In: Y. Jin (Eds.) Multi-Objective Machine Learning. Studies in Computational Intelligence 16, Springer-Verlag, 2006, 507-530			bib

 Conference Contributions

Jump to Year:
        2008  2007  2006  2005  2004  2003  2001  2000  1999  1998
        1997  1994

2008
	F.J. Berlanga, M.J. del Jesus, F. Herrera. A novel genetic cooperative-competitive fuzzy rule based learning method using genetic programming for high dimensional problems. 3rd International Workshop on Genetic and Evolving Fuzzy Systems (GEFS08). WittenBommerholz (Germany, 2008) 101-106			bib
				bib
				bib
	H. Ishibuchi, Y. Kaisho, Y. Nojima. Designing fuzzy rule-based classifiers that can visually explain their classification results to human users. 3rd International Workshop on Genetic and Evolving Fuzzy Systems (GEFS08). WittenBommerholz (Germany, 2008) 5-10			bib
	I. Kuwajima, H. Ishibuchi, Y. Nojima. Effectiveness of designing fuzzy rule-based classifiers from Pareto-optimal rules. 2008 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE08). Hong Kong (China, 2008) 1185-1192			bib
2007
	M.S. Abadeh, J. Habibi. Computer intrusion detection using an iterative fuzzy rule learning approach. 2007 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE07). London (UK, 2007) 1-6			bib
	J.J. Aguilera, M. Chica, M.J. del Jesus, F. Herrera. Niching genetic feature selection algorithms applied to the design of fuzzy rule-based classification systems. 2007 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE07). London (UK, 2007) 1794-1799			bib
				bib
	K. Almejalli, K. Dahal, A. Hossain. GA-based learning algorithms to identify fuzzy rules for fuzzy neural networks. 7th International Conference on Intelligent Systems Design and Applications (ISDA07). Rio de Janeiro (Brazil, 2007) 289-294			bib
	H. Ishibuchi, I. Kuwajima, Y. Nojima. Relation between pareto-optimal fuzzy rules and pareto-optimal fuzzy rule sets. The 2007 IEEE Symposium on Computational Intelligence in Multicriteria Decision Making (MCDM07). Honolulu (USA, 2007) 42-49			bib
	Y. Nojima, I. Kuwajima, H. Ishibuchi. Data set subdivision for parallel distributed implementation of genetic fuzzy rule selection. 2007 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE07). London (UK, 2007) 1-6			bib
	A. Yang, L. Jiang, Y. Zhou. A KFCM-based fuzzy classifier. Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD07). Haikou (China, 2007) 80-84			bib
	A.-M. Yang, X.-G. Li, L.-M. Jiang, Y.-M. Zhou, Q.-Q. Li. A method of generating rules for a kernel fuzzy classifier. Sixth International Conference on Machine Learning and Cybernetics (ICMLC07). Hong Kong (China, 2007) 2695-2700			bib
2006
	M. Bereta, T. Burczynski. MAICS: Multilevel artificial immune classification system. The Eighth International Conference on Artificial Intelligence and Soft Computing (ICAISC06). Lecture Notes in Computer Science 4029, Springer 2006, Zakopane (Poland, 2006) 563-572			bib
	F.J. Berlanga, M.J. del Jesus, M.J. Gacto, F. Herrera. A genetic-programming-based approach for the learning of compact fuzzy rule-based classification systems. The Eighth International Conference on Artificial Intelligence and Soft Computing (ICAISC06). Lecture Notes in Computer Science 4029, Springer 2006, Zakopane (Poland, 2006) 182-191			bib
	J.-M. Gil, S.-H. Lee. Genetic-fuzzy modeling on high dimensional spaces. 10th International Conference on Knowledge-Based & Intelligent Information & Engineering Systems (KES 2006). Lecture Notes in Computer Science 4251, Springer 2006, Bournemouth (UK, 2006) 1147-1154			bib
	H. Ishibuchi, Y. Nojima, I. Kuwajim. Finding simple fuzzy classification systems with high interpretability through multiobjective rule selection. 10th International Conference on Knowledge-Based & Intelligent Information & Engineering Systems (KES 2006). Lecture Notes in Computer Science 4252, Springer 2006, Bournemouth (UK, 2006) 86-93			bib
	H. Ishibuchi, Y. Nojima, I. Kuwajima. Comparison of search ability between genetic fuzzy rule selection and fuzzy genetics-based machine learning. 2006 International Symposium on Evolving Fuzzy Systems (EFS06). Lake District (UK, 2006) 125-130			bib
	H. Ishibuchi, Y. Nojima, I. Kuwajima. Fuzzy data mining by heuristic rule extraction and multiobjective genetic rule selection. 2006 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE06). Vancouver (Canada, 2006) 1633-1640			bib
	H. Ishibuchi, Y. Nojima, I. Kuwajima. Genetic rule selection as a postprocessing procedure in fuzzy data mining. 2006 International Symposium on Evolving Fuzzy Systems (EFS06). Lake District (UK, 2006) 286-291			bib
	J.-H. Park, D. Stonier, J.-H. Kim, B.-H. Ahn, M.-G. Jeon. Recombinant rule selection in evolutionary algorithm for fuzzy path planner of robot soccer. 29th Annual German Conference on Artificial Intelligence (KI06). Lecture Notes in Computer Science 4314, Springer-Verlag 2006, Bremen (Germany, 2006) 317-330			bib
	Z.-Y. Xing, Y.-L. Hou, Y. Zhang, L.-M. Jia, Y. Hou. A multi-objective cooperative coevolutionary algorithm for constructing accurate and interpretable fuzzy systems. 2006 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE06). Vancouver (Canada, 2006) 1404-1410			bib
	X. Zong-yi, H. Yuan-long, T. Zhong-zhi, J. Li-min. Construction of fuzzy classification system based on multi-objective genetic algorithm. Sixth International Conference on Intelligent Systems Design and Applications (ISDA06). Jinan (China, 2006) 1029-1034			bib
2005
	P.A.D. Castro, H.A. Camargo. Focusing on interpretability and accuracy of a genetic fuzzy system. The 2005 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2005). Reno (USA, 2005) 696-701			bib
	H. Ishibuchi, Y. Nojima. Performance evaluation of evolutionary multiobjective approaches to the design of fuzzy rule-based ensemble classifiers. Fifth International Conference on Hybrid Intelligent Systems (HIS05). Rio de Janeiro (Brazil, 2005) 271-276			bib
	H. Ishibuchi, Y. Nojima. Comparison between fuzzy and interval partitions in evolutionary multiobjective design of rule-based classification systems. The 2005 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2005). Reno (USA, 2005) 430-435			bib
2004
	H. Ishibuchi, T. Yamamoto. Multi-objective evolutionary design of fuzzy rule-based systems. 2004 IEEE International Conference on Systems, Man and Cybernetics (SMC 2004). The Hague (The Netherlands, 2004) 2362-2367			bib
2003
	T. Yamamoto, H. Ishibuchi. Performance evaluation of three-objective genetic rule selection. The 2003 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2003). St Louis (USA, 2003) 149-154			bib
2001
				bib
2000
	H. Ishibuchi, T. Nakashima, T. Kuroda. Hybrid fuzzy GBML algorithm for designing compact fuzzy rule-based classification systems. The 2000 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2000). San Antonio (USA, 2000) 706-711			bib
	H. Roubos, M. Setnes. Compact fuzzy models through complexity reduction and evolutionary optimization. IEEE International Conference on Fuzzy Systems 2000 (Fuzz-IEEE 2000). San Antonio (USA, 2000) 762-767			bib
1999
	H. Ishibuchi, T. Sotani, T. Murata. Tradeoff between the performance of fuzzy rule-based classification systems and the number of fuzzy if-then rules. 1999 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS 1999). New York (USA, 1999) 125-129			bib
1998
	H. Ishibuchi, T. Murata. Multi-objective genetic local search for minimizing the number of fuzzy rules for pattern classification problems. The 1998 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 1998). Anchorage (USA, 1998) 1100-1105			bib
1997
	H. Ishibuchi, M. Nii, T. Murata. Linguistic rule extraction from neural networks and genetic-algorithm-based rule selection. The 1997 IEEE International Conference on Neural Networks. Houston (USA, 1997) 2390-2395			bib
1994
	H. Ishibuchi, K. Nozaki, N. Yamamoto, H. Tanaka. Acquisition of fuzzy classification knowledge using genetic algorithms. The 1994 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 1994). Orlando (USA, 1994) 1963-1968			bib

 Journal Contributions: Published

Jump to Year:
        2008  2007  2006  2005  2004  2003  2002  2001  2000  1999
        1998  1997  1994

2008
	R. Naresh, V. Sharma, M. Vashisth. An integrated neural fuzzy approach for fault diagnosis of transformers. IEEE Transactions on Power Delivery 23:4 (2008) 2017-2024			bib
	S. Nefti, M. Oussalah, U. Kaymak. A new fuzzy set merging technique using inclusion-based fuzzy clustering. IEEE Transactions on Fuzzy Systems 16:1 (2008) 145-161			bib
	N.R. Pal, S. Saha. Simultaneous structure identification and fuzzy rule generation for Takagi-Sugeno models. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 38:6 (2008) 1626-1638			bib
	P. Salgado. Rule generation for hierarchical collaborative fuzzy system. Applied Mathematical Modelling 32:7 (2008) 1159-1178			bib
	E. Schmitt, V. Bombardier, L. Wendling. Improving fuzzy rule classifier by extracting suitable features from capacities with respect to the Choquet integral. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 38:5 (2008) 1195-1206			bib
2007
	A. Bouchachia, R. Mittermeir. Towards incremental fuzzy classifiers. Soft Computing 11:2 (2007) 193-207			bib
	J.L. Castro, L.D. Flores-Hidalgo, C.J. Mantas, J.M. Puche. Extraction of fuzzy rules from support vector machines. Fuzzy Sets and Systems 158:18 (2007) 2057-2077			bib
	Y. Hou, J.M. Zurada, W. Karwowski, W.S. Marras, K. Davis. Identification of key variables using fuzzy average with fuzzy cluster distribution. IEEE Transactions on Fuzzy Systems 15:4 (2007) 673-685			bib
	S.-M. Zhou, J.Q. Gan. Constructing L2-SVM-based fuzzy classifiers in high-dimensional space with automatic model selection and fuzzy rule ranking. IEEE Transactions on Fuzzy Systems 15:3 (2007) 398-409			bib
2006
	C.-T. Lin, C.-M. Yeh, S.-F. Liang, J.-F. Chung, N. Kumar. Support-vector-based fuzzy neural network for pattern classification. IEEE Transactions on Fuzzy Systems 14:1 (2006) 31-41			bib
2005
	J.G. Castellano, A.M. Fanelli, C. Mencar, C. Castiello. Knowledge discovery by a neuro-fuzzy modeling framework. Fuzzy Sets and Systems 149 (2005) 187-207			bib
	M.K. Ciliz. Rule base reduction for knowledge-based fuzzy controllers with application to a vacuum cleaner. Expert Systems with Applications 28:1 (2005) 175-184			bib
2004
	P. Carmona, J.L. Castro, J.M. Zurita. FRIwE: Fuzzy Rule Identification With Exceptions. IEEE Transactions on Fuzzy Systems 12:1 (2004) 140-151			bib
	D. Chakraborty, N.R. Pal. A neuro-fuzzy scheme for simultaneous feature selection and fuzzy rule-based classification. IEEE Transactions on Neural Networks 15:1 (2004) 110-123			bib
	M.-Y. Chen, D.A. Linkens. Rule-base self-generation and simplification for data-driven fuzzy models. Fuzzy Sets and Systems 142:2 (2004) 243-265			bib
	W. Duch, R. Setiono, J.M. Zurada. Computational intelligence methods for rule-based data understanding. Proceedings of the IEEE 92:5 (2004) 771-805			bib
	X. Hong, C.J. Harris, S. Chen. Robust Neurofuzzy Rule Base Knowledge Extraction and Estimation Using Subspace Decomposition Combined with Regularization and D-Optimality. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 34:1 (2004) 598-608			bib
	Q. Shen, R. Jensen. Selecting informative features with fuzzy-rough sets and its application for complex systems monitoring. Pattern Recognition 37:7 (2004) 1351-1363			bib
2003
				bib
	M.R. Berthold. Mixed fuzzy rule formation. International Journal of Approximate Reasoning 32:2-3 (2003) 67-84			bib
	Y. Chen, J.Z. Wang. Support Vector Learning for Fuzzy Rule-Based Classification Systems. IEEE Transactions on Fuzzy Systems 11:6 (2003) 716-728			bib
	X. Hong, C.J. Harris. A neurofuzzy network knowledge extraction and extended Gram-Schmidt algorithm for model subspace decomposition. IEEE Transactions on Fuzzy Systems 11:4 (2003) 528-541			bib
	J.A. Roubos, M. Setnes, J. Abonyi. Learning fuzzy classification rules from labeled data. Information Sciences 150:1-2 (2003) 77-93			bib
2002
				bib
				bib
	R.P. Li, M. Mukaidono, I. Burhan. A fuzzy neural network for pattern classification and feature selection. Fuzzy Sets and Systems 130:1 (2002) 101-108			bib
	Q. Shen, A. Chouchoulas. A rough-fuzzy approach for generating classification rules. Pattern Recognition 35:11 (2002) 2425-2438			bib
2001
	V. Ravi, H.J. Zimmermann. A neural network and fuzzy rule base hybrid for pattern classification. Soft Computing - A Fusion of Foundations, Methodologies and Applications 5:2 (2001) 152-159			bib
	M. Setnes, R. Babuska. Rule base reduction: Some comments on the use of orthogonal transforms. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 31:2 (2001) 199-206			bib
2000
	V. Ravi, H.J. Zimmermann. Fuzzy rule based classification with FeatureSelector and modified threshold accepting. European Journal of Operational Research 123:1 (2000) 16-28			bib
	V. Ravi, P.J. Reddy, H.J. Zimmermann. Pattern classification with principal component analysis and fuzzy rule bases. European Journal of Operational Research 126:3 (2000) 526-533			bib
	Q. Shen, A. Chouchoulas. Modular approach to generating fuzzy rules with reduced attributes for the monitoring of complex systems. Engineering Applications of Artificial Intelligence 13:3 (2000) 263-278			bib
	R. Silipo, M.R. Berthold. Input features' impact on fuzzy decision processes. IEEE Transactions on Systems, Man and Cybernetics, Part B 30:6 (2000) 821-834			bib
1999
	L. Mikenina, H.J. Zimmermann. Improved feature selection and classification by the 2-additive fuzzy measure. Fuzzy Sets and Systems 107:2 (1999) 197-218			bib
	M. Ramze, B. Goedhart, B.P.F. Lelieveldt, J.H.C. Reiber. Fuzzy feature selection. Pattern Recognition 32:12 (1999) 2011-2019			bib
	J. Yen, L. Wang. Simplifying fuzzy rule-based models using orthogonal transformation methods. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 29:1 (1999) 13-24			bib
1998
	J. Martens, G. Wets, C. Mues. An initial comparison of a fuzzy neural classifier and a decision tree based classifier. Expert Systems with Applications 15:3-4 (1998) 375-381			bib
	M. Setnes, R. Babuska, U. Kaymak, H.R. Van Nauta Lemke. Similarity measures in fuzzy rule base simplification. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 28:3 (1998) 376-386			bib
1997
	R. Thawonmas, S. Abe. A novel approach to feature selection based on analysis of class regions. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 27:2 (1997) 196-207			bib
1994
	C.-T. Sun. Rule-base structure identification in an adaptive-network-based fuzzy inference system. EEE Transactions on Fuzzy Systems 2:1 (1994) 64-73			bib
	E. Tunstel, S. Hockemeier, M. Jamshidi. Fuzzy control of a hovercraft platform. Engineering Applications of Artificial Intelligence 7:5 (1994) 513-519			bib

 Conference Contributions

Jump to Year:   2008  2007  2006  2004  1997  1994

2008
	S.-M. Zhou, R.I. John, X.-Y. Wang, J.M. Garibaldi, I.O. Ellis. Compact fuzzy rules induction and feature extraction using SVM with particle swarms for breast cancer treatments. 2008 IEEE Congress on Evolutionary Computation (CEC08). Hong Kong (China, 2008) 1469-1475			bib
2007
	O. Dehzangi, M.J. Zolghadri, S. Taheri, S.M. Fakhrahmad. Efficient fuzzy rule generation: A new approach using data mining principles and rule weighting. Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD07). Haikou (China, 2007) 134-139			bib
	S.M. Fakhrahmad, A. Zare, M.Z. Jahromi. Constructing accurate fuzzy rule-based classification systems using apriori principles and rule-weighting. 8th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL07). Lecture Notes in Computer Science 4881, Springer-Verlag 2007, Birmingham (UK, 2007) 547-556			bib
	N.R. Pal. A fuzzy rule based approach to identify biomarkers for diagnostic classification of cancers. 2007 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE07). London (UK, 2007) 1-6			bib
	B. Pizzileo, K. Li. A new fast algorithm for fuzzy rule selection. 2007 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE07). London (UK, 2007) 1-6			bib
2006
	N.E. Mitrakis, J.B. Theocharis. A self-organizing fuzzy polynomial neural network - Multistage classifier. The 2006 International Symposium on Evolving Fuzzy Systems (EFS06). Lake District (UK, 2006) 74-79			bib
	D. Wang, X.-J. Zeng, J.A. Keane. Learning for hierarchical fuzzy systems based on the gradient-descent method. 2006 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE06). Vancouver (Canada, 2006) 92-99			bib
2004
	O. Ciftcioglu. Note on orthogonal transformation methods for simplifying fuzzy rule-based models. 2004 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS 2004). Banff (Canada, 2004) 756-761			bib
	H. Ishibuchi, T. Yamamoto. Heuristic extraction of fuzzy classification rules using data mining techniques: An empirical study on benchmark data sets. The 2004 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2004). Budapest (Hungary, 2004) 161-166			bib
1997
	H. Ishibuchi, T. Nakashima, T. Morisawa. Simple fuzzy rule-based classification systems perform well on commonly used real-world data sets. 1997 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS97). Syracuse (USA, 1997) 251-256			bib
1994
	K. Nozaki, H. Ishibuchi, H. Tanaka. Selecting fuzzy rules with forgetting in fuzzy classification systems. The 1994 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 1994). Orlando (USA, 1994) 618-623			bib

If you would like to add a new reference in this specific topic, please contact:
     Francisco José Berlanga Rivera ()