Fuzzy rule clustering

被引：0
|
作者：
Salgado, P [1 ]
机构：
[1] Univ Tras Montes & Alto Douro, Dept Engn, P-5000 Vila Real, Portugal
来源：
2001 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5: E-SYSTEMS AND E-MAN FOR CYBERNETICS IN CYBERSPACE | 2002年
关键词：
fuzzy clustering; hierarchical fuzzy model; similarity measure;
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：
The concept of relevance has been proposed as a measure of the relative importance of sets of rules [1][2], allowing the development of a new methodology of organising the linguistic information: SLIM (Separation of Linguistic Information Methodology) [1][2]. Based on this concept and on this methodology, a new Fuzzy Clustering of Fuzzy Rules Algorithm (FCFRA) is proposed and applied to organise the fuzzy IF ... THEN rules. The proposed FCFRA algorithm has been successfully applied to illustrate a segmentation operation in the "fuzzy rules domain", using the Abington Cross image.
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页码：2421 / 2427
页数：7
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