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
收藏
页码：238 / +
页数：3
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