Genetic learning of fuzzy rule-based classification systems cooperating with fuzzy reasoning methods
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[1] María José del Jesús,et al. MOGUL: A methodology to obtain genetic fuzzy rule-based systems under the iterative rule learning approach , 1999, Int. J. Intell. Syst..
[2] Ralph R. Martin,et al. A Sequential Niche Technique for Multimodal Function Optimization , 1993, Evolutionary Computation.
[3] M. Lozano,et al. MOGUL: A methodology to obtain genetic fuzzy rule‐based systems under the iterative rule learning approach , 1999 .
[4] C. A. Murthy,et al. Formulation of a multivalued recognition system , 1992, IEEE Trans. Syst. Man Cybern..
[5] Shigeo Abe,et al. A fuzzy classifier with ellipsoidal regions , 1997, IEEE Trans. Fuzzy Syst..
[6] Hong Yan,et al. Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition , 1996, Advances in Fuzzy Systems - Applications and Theory.
[7] F. Herrera,et al. A proposal on reasoning methods in fuzzy rule-based classification systems , 1999 .
[8] Sankar K. Pal,et al. Fuzzy self-organization, inferencing, and rule generation , 1996, IEEE Trans. Syst. Man Cybern. Part A.
[9] John H. Holland,et al. Cognitive systems based on adaptive algorithms , 1977, SGAR.
[10] Hisao Ishibuchi,et al. Efficient fuzzy partition of pattern space for classification problems , 1993 .
[11] Antonio González Muñoz,et al. Multi-stage genetic fuzzy systems based on the iterative rule learning approach , 1997 .
[12] Ludmila I. Kuncheva,et al. On the Equivalence between fuzzy and Statistical Classifiers , 1996, Int. J. Uncertain. Fuzziness Knowl. Based Syst..
[13] Didier Dubois,et al. A review of fuzzy set aggregation connectives , 1985, Inf. Sci..
[14] Francisco Herrera,et al. A three-stage evolutionary process for learning descriptive and approximate fuzzy-logic-controller knowledge bases from examples , 1997, Int. J. Approx. Reason..
[15] Raúl Pérez,et al. Completeness and consistency conditions for learning fuzzy rules , 1998, Fuzzy Sets Syst..
[16] L. A. ZADEH,et al. The concept of a linguistic variable and its application to approximate reasoning - I , 1975, Inf. Sci..
[17] H. Ishibuchi,et al. Distributed representation of fuzzy rules and its application to pattern classification , 1992 .
[18] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[19] María José del Jesús,et al. A proposal on reasoning methods in fuzzy rule-based classification systems , 1999, Int. J. Approx. Reason..
[20] Zheru Chi,et al. Handwritten numeral recognition using self-organizing maps and fuzzy rules , 1995, Pattern Recognit..
[21] D. Fogel. Evolutionary algorithms in theory and practice , 1997, Complex..
[22] Tsu-Tian Lee,et al. On the design of a classifier with linguistic variables as inputs , 1983 .
[23] L. Valverde,et al. On Some Logical Connectives for Fuzzy Sets Theory , 1983 .
[24] Kalyanmoy Deb,et al. An Investigation of Niche and Species Formation in Genetic Function Optimization , 1989, ICGA.
[25] LiMin Fu,et al. Rule Generation from Neural Networks , 1994, IEEE Trans. Syst. Man Cybern. Syst..
[26] Sholom M. Weiss,et al. Computer Systems That Learn , 1990 .
[27] H. Ishibuchi,et al. Voting schemes for fuzzy-rule-based classification systems , 1996, Proceedings of IEEE 5th International Fuzzy Systems.
[28] Aiko M. Hormann,et al. Programs for Machine Learning. Part I , 1962, Inf. Control..
[29] Lucien Duckstein,et al. Fuzzy Rule-Based Modeling with Applications to Geophysical, Biological and Engineering Systems , 1995 .
[30] Francisco Herrera,et al. A learning process for fuzzy control rules using genetic algorithms , 1998, Fuzzy Sets Syst..
[31] Francisco Herrera,et al. Encouraging Cooperation in the Genetic Iterative Rule Learning Approach for Qualitative Modeling , 1999 .
[32] Stephen F. Smith,et al. A learning system based on genetic adaptive algorithms , 1980 .
[33] Teuvo Kohonen,et al. Self-Organizing Maps , 2010 .