Evolutionary modular fuzzy system

被引：9

作者：

Shi, YH ^{[1
]}

Eberhart, R ^{[1
]}

Chen, YB ^{[1
]}

机构：

[1] Indiana Univ Purdue Univ, Dept Elect Engn, Indianapolis, IN 46202 USA

来源：

1998 IEEE INTERNATIONAL CONFERENCE ON EVOLUTIONARY COMPUTATION - PROCEEDINGS | 1998年

关键词：

D O I：

10.1109/ICEC.1998.699764

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Generalization is one of the most important issues in designing fuzzy systems using evolutionary computational techniques. It is not always true that the evolved system with the highest fitness has the best generalization ability Generally it is difficult, if not impossible, to fell which system among the final population of evolved systems has the best generalization ability. In this paper, an evolutionary modular fuzzy system is proposed. Instead of selecting a single system, a set of systems is selected from the final population. The selected systems are combined together with each sewing as a module of the final system and having a contribution to the final system's performance proportional to its fitness. Preliminary simulation studies are presented to illustrate the effectiveness of this approach.

引用

页码：387 / 391

页数：5