Fuzzy interpolative reasoning via cutting and transformations techniques

被引：0

作者：

Ko, Yaun-Kai ^{[1
]}

Chen, Shyi-Ming ^{[1
]}

机构：

[1] Natl Taiwan Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan

来源：

NEW TRENDS IN APPLIED ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2007年 / 4570卷

关键词：

fuzzy interpolative reasoning; cutting and transformation techniques; increment and ratio transformations; sparse fuzzy rule-based systems;

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：

Fuzzy interpolative reasoning techniques can reduce the complexity of a sparse fuzzy rule-based system. In this paper, we present a new fuzzy interpolative reasoning method via cutting and transformations techniques for sparse fuzzy rule-based systems. It produces more reasonable reasoning consequences than the ones presented in [1] and [3]. The proposed method provides a useful way to deal with fuzzy interpolative reasoning in sparse fuzzy rule-based systems.

引用

页码：238 / +

页数：3

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