A fuzzy soft set based approximate reasoning method

被引：6
|
作者：
Qin, Keyun [1 ]
Yang, Jilin [2 ]
Liu, Zhicai [1 ]
机构：
[1] Southwest Jiaotong Univ, Coll Math, Chengdu 610031, Sichuan, Peoples R China
[2] Sichuan Normal Univ, Coll Fundamental Educ, Chengdu, Sichuan, Peoples R China
来源：
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2017年 / 32卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Fuzzy set; soft set; fuzzy soft implication relation; triple I method; left-continuous t-norm; SIMILARITY MEASURE; GENERAL FRAME; INFERENCE;
D O I：
10.3233/JIFS-16088
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Soft set theory, proposed by Molodtsov, has been regarded as an effective mathematical tool for dealing with uncertainties. This paper is devoted to the discussion of fuzzy soft set based approximate reasoning. First, based on fuzzy implication operators, the notion of fuzzy soft implication relation between fuzzy soft sets is introduced. The composition method of fuzzy soft implication relations is provided. Second, Triple I methods for fuzzy soft modus ponens (FSMP)and fuzzy soft modus tollens (FSMT) are investigated. Computational formulas for FSMP and FSMT with respect to left-continuous t-norms and its residual implication are presented. At last, the reversibility properties of Triple I methods are analyzed.
引用
收藏
页码：831 / 839
页数：9
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