A Similarity-based Fuzzy Soft Reasoning Method

被引：0
|
作者：
Wang, Lu [1 ]
Xue, Binbin [1 ]
Qin, Keyun [1 ]
机构：
[1] Southwest Jiaotong Univ, Coll Math, Chengdu 611756, Sichuan, Peoples R China
来源：
2017 12TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (IEEE ISKE) | 2017年
基金：
中国国家自然科学基金;
关键词：
Similarity measure; Fuzzy soft set; Implication function; t-Norm; DECISION-MAKING; MEDICAL DIAGNOSIS; SET; COMBINATION; 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：
The soft set theory proposed by Molodtsov is regarded as an effective mathematical tool for dealing with uncertainties. This paper discusses the approximate reasoning based on the similarity measure for fuzzy soft set. The approximate reasoning methods based on the similarity measure for fuzzy soft modus ponens (FSMP) are investigated. The corresponding computational formulas for these methods are presented. Furthermore, the reductive properties and the monotonic properties of these methods are analyzed.
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页数：7
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