Implementation of evolutionary fuzzy systems

被引：284

作者：

Shi, YH ^{[1
]}

Eberhart, R ^{[1
]}

Chen, YB ^{[1
]}

机构：

[1] Indiana Univ Purdue Univ, Purdue Sch Engn & Technol, Indianapolis, IN 46202 USA

来源：

IEEE TRANSACTIONS ON FUZZY SYSTEMS | 1999年 / 7卷 / 02期

关键词：

fuzzy expert systems; genetic algorithm; membership;

D O I：

10.1109/91.755393

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, evolutionary fuzzy systems are discussed in which the membership function shapes and types and the fuzzy rule set including the number of rules inside it are evolved using a genetic (evolutionary) algorithm. In addition, the genetic parameters (operators) of the evolutionary algorithm are adapted via a fuzzy system. Benefits of the methodology are illustrated in the process of classifying the iris data set. Possible extensions of the methods are summarized.

引用

页码：109 / 119

页数：11

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