A genetic algorithm for optimizing Takagi-Sugeno fuzzy rule bases

被引：64

作者：

Siarry, P ^{[1
]}

Guely, F

机构：

[1] Ecole Cent Paris, Grande Voie Vignes, F-92295 Chatenay Malabry, France

[2] Schneider Elect, F-92000 Nanterre, France

来源：

FUZZY SETS AND SYSTEMS | 1998年 / 99卷 / 01期

关键词：

fuzzy logic; genetic algorithms; Takagi-Sugeno rules; optimization;

D O I：

10.1016/S0165-0114(97)00003-1

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We show that a genetic algorithm can tune the parameters of the membership functions and outputs of a Takagi-Sugeno fuzzy rule base. The method is systematically tested for the approximation of one-input analytical function. (C) 1998 Published by Elsevier Science B.V. All rights reserved.

引用

页码：37 / 47

页数：11

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