A genetic reduction of feature space in the design of fuzzy models

Applied Soft Computing Journal

Volumn 12, Issue 9, 2012, Pages 2801-2816

  Pedrycz, Witold ^a,b,c   Song, Mingli ^a,b  

^a UNIVERSITY OF ALBERTA   (Canada)

^b KING ABDULAZIZ UNIVERSITY   (Saudi Arabia)

^c SYSTEMS RESEARCH INSTITUTE   (Poland)

Author keywords

Feature reduction; Fuzzy clustering; Fuzzy models; Genetic algorithm

Indexed keywords

DESIGN ISSUES; DESIGN METHODOLOGY; EXPERIMENTAL STUDIES; FEATURE REDUCTION; FEATURE SPACE; FUZZIFICATIONS; FUZZY C-MEANS; FUZZY MODELING; FUZZY MODELS; INPUT SPACE; INTERPRETABILITY; LOCAL LINEAR MODELS; LOCAL MODEL; NUMERICAL ASPECTS; OBJECTIVE FUNCTIONS; OPTIMIZATION SCHEME; REDUCED DIMENSIONALITY; REDUCED INPUTS; RULE BASED; SPACE REDUCTIONS; SYNTHETIC DATA;

FUZZY CLUSTERING; GENETIC ALGORITHMS; INFORMATION GRANULES;

DESIGN;

EID: 84863485089     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2012.03.055     Document Type: Article

References (19)

1. R. Alcala, P. Ducange, F. Herrera, B. Lazzerini, and F. Marcelloni A multiobjective evolutionary approach to concurrently learn rule and data bases of linguistic fuzzy-rule-based systems IEEE Transactions on Fuzzy Systems 17 2009 1106 1122
2. J.C. Bezdek Pattern Recognition with Fuzzy Objective Function Algorithms 1981 Plenum Press New York
3. P.P. Bonissone, A. Varma, K.S. Aggour, and F. Xue Design of local fuzzy models using evolutionary algorithms Computational Statistics and Data Analysis 51 2006 398 416 (Pubitemid 44634797)
4. L. Chen, C.L.P. Chen, and W. Pedrycz A gradient-descent-based approach for transparent linguistic interface generation in fuzzy models IEEE Transactions on Systems, Man, and Cybernetics Part B 40 5 2010 1219 1230
5. M. Delgado, F. Gomez-Skarmeta, and F. Martin A fuzzy clustering based rapid prototyping for fuzzy rule-based modeling IEEE Transactions on Fuzzy Systems 5 1997 223 233 (Pubitemid 127768510)
6. M. Eftekhari, S.D. Katebi, M. Karimi, and A.H. Jahanmiri Eliciting transparent fuzzy model using differential evolution Applied Soft Computing 8 2008 466 476 (Pubitemid 47374579)
7. A.F. Gobi, and W. Pedrycz Fuzzy modeling through logic optimization International Journal of Approximate Reasoning 45 2007 488 510 (Pubitemid 46880533)
8. H. Ishibuchi, and Y. Nojima Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning International Journal of Approximate Reasoning 44 2007 4 31
9. X. Liang, and W. Pedrycz Logic-based fuzzy networks: a study in system modeling with triangular norms and uninorms Fuzzy Sets and Systems 160 24 2009 3475 3502
10. H.S. Park, W. Pedrycz, and S.K. Oh Granular neural networks and their development through context-based clustering and adjustable dimensionality of receptive fields IEEE Transactions on Neural Networks 20 10 2009 1604 1616
11. A. Pedrycz, F. Dong, and K. Hirota Relational models of fuzzy clusters Proceedings of IEEE Conference on Systems, Man, and Cybernetics Singapore 2007
12. W. Pedrycz Knowledge-based Clustering: From Data to Information Granules 2005 John Wiley Hoboken, NJ
13. D.T. Pham, and M. Castellani Evolutionary learning of fuzzy models Engineering Applications of Artificial Intelligence 19 2006 583 592 (Pubitemid 44292513)
14. H. Roubos, and M. Setnes Compact and transparent fuzzy models and classifiers through iterative complexity reduction IEEE Transactions on Fuzzy Systems 9 2001 516 524 (Pubitemid 32933039)
15. L.A. Zadeh Towards a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic Fuzzy Sets and Systems 90 1997 111 117
16. M.A. Vélez, O. Sánchez, S. Romero, and J.M. Andújar A new methodology to improve interpretability in neuro-fuzzy TSK models Applied Soft Computing 10 2 2010 578 591
17. E. Araujo, and L.S. Coelho Particle swarm approaches using Lozi map chaotic sequences to fuzzy modeling of an experimental thermal-vacuum system Applied Soft Computing 8 4 2008 1354 1364
18. L. Zhao, F. Qian, Y. Yang, Y. Zeng, and H. Su Automatically extracting T-S fuzzy models using cooperative random learning particle swarm optimization Applied Soft Computing 10 3 2010 938 944
19. S.K. Oh, W. Pedrycz, and S.B. Roh Hybrid fuzzy set-based polynomial neural networks and their development with the aid of genetic optimization and information granulation Applied Soft Computing 9 3 2009 1068 1089