Design of fuzzy classification system using genetic algorithms

被引：0

作者：

Wong, CC ^{[1
]}

Chen, CC ^{[1
]}

Lin, BC ^{[1
]}

机构：

[1] Tamkang Univ, Dept Elect Engn, Taipei Hsien, Taiwan

来源：

NINTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2000), VOLS 1 AND 2 | 2000年

关键词：

fuzzy classification; genetic algorithms;

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：

This paper proposes a GA-based method to construct an appropriate fuzzy classification system to maximize the number of correctly classified patterns and minimize the number of fuzzy rules. In this method, a fuzzy classification system is coded as an individual in the GA. A fitness function is defined such that it can guide the search procedure to select an appropriate fuzzy classification system to maximize the number of correctly classified patterns and minimize the number of fuzzy rules. Finally, a two-class classification problem is utilized to illustrate the efficiency of the proposed method.

引用

页码：297 / 301

页数：5

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