Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base

被引：165
|
作者：
Cordón, O
Herrera, F
Villar, P
机构：
[1] Univ Granada, Dept Comp Sci & Artificial Intelligence, E-18071 Granada, Spain
[2] Univ Vigo, ESEI, Dept Comp, Orense 32004, Spain
来源：
IEEE TRANSACTIONS ON FUZZY SYSTEMS | 2001年 / 9卷 / 04期
关键词：
fuzzy rule-based systems; data base; learning; genetic algorithms;
D O I：
10.1109/91.940977
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new method is proposed to automatically learn the knowledge base (KB) by finding an appropiate data base (DB) by means of a genetic algorithm while using a simple generation method to derive the rule base (RB). Our genetic process learns the number of linguistic terms per variable and the membership function parameters that define their semantics, while a rule base generation method learns the number of rules and their composition.
引用
收藏
页码：667 / 674
页数：8
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