About the use of fuzzy clustering techniques for fuzzy model identification

Abstract In this work we present an alternative approach to generate fuzzy rules with a functional consequent associated to the TSK fuzzy model. In our case, using fuzzy clustering algorithms that look for linear behaviours in the product space of the input-output data, we analyse different methods to generate the associated fuzzy rules using in some cases multidimensional reference fuzzy sets in the product space of the input variables and in other cases fuzzy sets in each of the different dimensions. In any case the rules being generated correspond to a TSK fuzzy model.

[1]  Francisco Herrera,et al.  Tuning fuzzy logic controllers by genetic algorithms , 1995, Int. J. Approx. Reason..

[2]  Liang Wang,et al.  Complex systems modeling via fuzzy logic , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[3]  Li-Xin Wang.  Training of fuzzy logic systems using nearest neighborhood clustering , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[4]  H. Berenji,et al.  Clustering in product space for fuzzy inference , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[5]  Sankar K. Pal,et al.  Fuzzy models for pattern recognition , 1992 .

[6]  Dimitar Filev,et al.  Unified structure and parameter identification of fuzzy models , 1993, IEEE Trans. Syst. Man Cybern..

[7]  P. Siarry,et al.  A centered formulation of Takagi-Sugeno rules for improved learning efficiency , 1994 .

[8]  領家 美奈,et al.  A Possibilistic Approach to Clustering Raghu Krishnapuram and James M. Keller IEEE Transactions on Fuzzy Systems, Vol.1,Vol.2,pp.98-110,1993 , 1995 .

[9]  M. Sugeno,et al.  A review and comparison of six reasoning methods , 1993 .

[10]  Ronald R. Yager,et al.  Template-Based Fuzzy Systems Modeling , 1994, J. Intell. Fuzzy Syst..

[11]  Patrick K. Simpson,et al.  Fuzzy min-max neural networks for function approximation , 1993, IEEE International Conference on Neural Networks.

[12]  Donald Gustafson,et al.  Fuzzy clustering with a fuzzy covariance matrix , 1978, 1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes.

[13]  W. Pedrycz.  An identification algorithm in fuzzy relational systems , 1984 .

[14]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[15]  Frank Klawonn,et al.  Constructing a fuzzy controller from data , 1997, Fuzzy Sets Syst..

[16]  Derek A. Linkens,et al.  Learning control using fuzzified self-organizing radial basis function network , 1993, IEEE Trans. Fuzzy Syst..

[17]  Joonwhoan Lee,et al.  Fuzzy-connective-based hierarchical aggregation networks for decision making , 1992 .

[18]  M. Delgado,et al.  Hierarchical clustering to validate fuzzy clustering , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[19]  Didier Dubois,et al.  Gradual inference rules in approximate reasoning , 1992, Inf. Sci..

[20]  Dimitar Filev,et al.  Generation of Fuzzy Rules by Mountain Clustering , 1994, J. Intell. Fuzzy Syst..

[21]  Kazuo Tanaka,et al.  Successive identification of a fuzzy model and its applications to prediction of a complex system , 1991 .

[22]  N. Karayiannis.  MECA: maximum entropy clustering algorithm , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[23]  E. H. Mamdani,et al.  Advances in the linguistic synthesis of fuzzy controllers , 1976 .

[24]  Andreas Kroll,et al.  Identification of functional fuzzy models using multidimensional reference fuzzy sets , 1996, Fuzzy Sets Syst..

[25]  Hisao Ishibuchi,et al.  Selecting fuzzy if-then rules for classification problems using genetic algorithms , 1995, IEEE Trans. Fuzzy Syst..

[26]  Bart Kosko,et al.  Fuzzy function approximation with ellipsoidal rules , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[27]  James C. Bezdek,et al.  Fuzzy Kohonen clustering networks , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[28]  Isak Gath,et al.  Unsupervised Optimal Fuzzy Clustering , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[29]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[30]  R. Babuška,et al.  A new identification method for linguistic fuzzy models , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[31]  Petri Vuorimaa,et al.  Fuzzy self-organizing map , 1994 .

[32]  Constantin V. Negoita,et al.  On Fuzzy Systems , 1978 .

[33]  Michio Sugeno,et al.  A fuzzy-logic-based approach to qualitative modeling , 1993, IEEE Trans. Fuzzy Syst..

[34]  R. de Figueiredo,et al.  Fuzzy system design through fuzzy clustering and optimal predefuzzification , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[35]  Raghu Krishnapuram.  Generation of membership functions via possibilistic clustering , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[36]  H. Zimmermann,et al.  Latent connectives in human decision making , 1980 .

[37]  James C. Bezdek,et al.  Fuzzy Kohonen clustering networks , 1994, Pattern Recognit..

[38]  Shyh Hwang,et al.  An identification algorithm in fuzzy relational systems , 1996, Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium.

[39]  W. Pedrycz,et al.  Construction of fuzzy models through clustering techniques , 1993 .

[40]  S. Chiu,et al.  A cluster estimation method with extension to fuzzy model identification , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[41]  Reza Langari,et al.  Fuzzy models, modular networks, and hybrid learning , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[42]  K. Hirota,et al.  Ordering, distance and closeness of fuzzy sets , 1993 .

[43]  Jerry M. Mendel,et al.  Back-propagation fuzzy system as nonlinear dynamic system identifiers , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.