Additive Fuzzy Functional Inference Methods

被引：0
作者：
Seki, Hirosato [1 ]
Mizumoto, Masaharu [2 ]
机构：
[1] Oaska Inst Technol, Dept Technol Management, Osaka, Japan
[2] Oaska Electron Commun Univ, Dept Engn Informat, Osaka, Japan
来源：
IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2010) | 2010年
关键词：
ARTIFICIAL NEURAL-NETWORKS; SYSTEMS; EQUIVALENCE; BOXES;
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 an additive fuzzy functional inference method which aggregates a final inference result by using sum operation rather max from inference results obtained by fuzzy rules whose consequent part consists of a fuzzy function. The additive fuzzy functional inference method is shown to be reduced to a functional inference method with a compatibility function which represents the characteristics such as area, base length and importantness of the fuzzy functinoal rule. Moreover, this paper shows that the fuzzy functional inference method with compatibility function includes ordinary T-S inference method and weighted fuzzy inference method.
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页数：6
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