直觉模糊集(数)间相似度量新方法  

New method for similarity measures between intutionistic fuzzy sets(values)

作　　者：全雪峰[1] 常梦星[1] 

机构地区：[1]南阳医学高等专科学校卫生管理系,河南南阳473061

出　　处：《计算机工程与应用》2015年第12期208-212,共5页Computer Engineering and Applications

基　　金：河南省教育厅科学技术研究重点项目(No.12B520039);南阳市科技攻关计划项目(No.2012GG014)

摘　　要：直觉模糊集概念产生于模糊集概念,自Atanassov提出这个概念以来,已得到了众多研究者的关注并被应用到不同的领域。作为直觉模糊理论的一个重要研究内容,研究者已在不同文献中提出多种不同的直觉模糊集相似度量方法,但这些方法在一些特殊情况下并不总是有效。指出了影响直觉模糊集(数)相似度量的因素,分析了现有方法存在不足的原因,提出了一种综合考虑隶属度、非隶属度、犹豫度、核及其相互影响后的新的相似度量方法,指出并证明了该方法所具有的新的性质。数字实例表明该方法可以克服现存几种方法的缺陷,结果符合人们直觉,具有更强的区分数据能力。The concept of intuitionistic fuzzy set originates from the concept of fuzzy set. It has drawn many researchers’ attentions since it is proposed by Atanassov, and has been applied into different fields. As an important research content of intuitionistic fuzzy theory, many different methods have been published by different researchers to measure the similarity between intuitionistic fuzzy sets. However, these methods are not always effective in some special cases. This paper points out the factors influencing similarity measurements between intuitionistic fuzzy sets（values）, analyzes the defects reasons of existing methods, proposes an improved method of similarity measurement which comprehensively considers membership, non-membership, hesitation, core, and their mutual influence, indicates and proves the new features of this method. Numerical results show that this proposed method solves the defects of existing methods, yielding result closer to peoples’intuitionistic. It provides stronger data distinguish ability.

关 键 词：模糊集 直觉模糊集 直觉模糊数 相似度量 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]