Fuzzy modeling using genetic algorithms with fuzzy entropy as conciseness measure

被引：4
作者：
Suzuki, T
Kodama, T
Furuhashi, T
Tsutsui, H
机构：
[1] Nagoya Univ, Dept Informat Elect, Chikusa Ku, Nagoya, Aichi 4648603, Japan
[2] Mie Univ, Dept Informat Engn, Tsu, Mie 5148507, Japan
[3] Yamatake Corp, Res & Dev Headquarters, Fujisawa, Kanagawa 2518522, Japan
来源：
INFORMATION SCIENCES | 2001年 / 136卷 / 1-4期
关键词：
fuzzy modeling; fuzzy entropy; genetic algorithms; conciseness measure; linguistic interpretability;
D O I：
10.1016/S0020-0255(01)00141-4
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a fuzzy modeling method using genetic algorithms (GAs) with a conciseness measure is presented. This paper introduces De Luca and Termini's fuzzy entropy to evaluate the shape of a membership function, and proposes another measure to evaluate the deviation of a membership function from symmetry. A combined measure is then derived from these two measures, and a new conciseness measure is defined for evaluation of the shape and allocation of the membership functions of a fuzzy model. Numerical results show that the new conciseness measure is effective for fuzzy modeling formulated as a multi-objective optimization problem. (C) 2001 Published by Elsevier Science Inc.
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收藏
页码：53 / 67
页数：15
相关论文
共 17 条
[1]  
Akaike H., 1973, 2 INT S INFORM THEOR, P267, DOI [DOI 10.1007/978-1-4612-1694-0_15, 10.1007/978-1-4612-1694-0_15]
[2]  
[Anonymous], 1989, GENETIC ALGORITHM SE
[3]   Semantic constraints for membership function optimization [J].
de Oliveira, JV .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 1999, 29 (01) :128-138
[4]   DEFINITION OF NONPROBABILISTIC ENTROPY IN SETTING OF FUZZY SETS THEORY [J].
DELUCA, A ;
TERMINI, S .
INFORMATION AND CONTROL, 1972, 20 (04) :301-&
[5]  
FONSECA CM, 1993, PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON GENETIC ALGORITHMS, P416
[6]  
LOUIS SJ, 1993, PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON GENETIC ALGORITHMS, P118
[7]  
MATSUSHITA S, 1996, P 1996 1 AS PAC C SI, P106
[8]  
Miyamoto S., 1997, PROC 7 INT FUZZY SYS, P86
[9]  
MIZUMOTO M, 1987, P 2 IFSA C, P143
[10]  
NOMURA H, 1992, P INT SYST S, P25
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