Evolutionary system identification via descriptive Takagi Sugeno fuzzy systems

被引：0
|
作者：
Renners, I [1 ]
Grauel, A [1 ]
机构：
[1] Univ Appl Sci, Dept Math, Ctr Computat Intelligence & Cognit Sci, D-59494 Soest, Germany
来源：
ADVANCES IN INTELLIGENT DATA ANALYSIS V | 2003年 / 2810卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
System identification is used to identify relevant input-output space relations. In this article the relations are used to model a descriptive Takagi-Sugeno fuzzy system. Basic terms of system identification, fuzzy systems and evolutionary computation are briefly reviewed. These concepts are used to present the implementation of an evolutionary algorithm which identifies (sub)optimal descriptive Takagi-Sugeno fuzzy systems according to given data. The proposed evolutionary algorithm is tested on the well known gas furnace data set and results are presented.
引用
收藏
页码：474 / 485
页数：12
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