基于正态分布函数的直觉模糊集的相似度量方法

New Method to Measure Similarity Between Intuitionistic Fuzzy Sets Based on Normal Distribution Functions

直觉模糊集合(intuitionistic fuzzy sets,简称IFSs)是模糊集(fuzzy sets,简称FSs)的拓展,IFSs间的相似度量是IFSs理论中的一个重要研究问题.在对现存的IFSs的相似度量方法进行研究的基础上,基于投票模型,提出了一种新的基于正态分布函数的相似度量方法,实例证明该方法既可以解决几种特殊的直觉模糊集合之间的相似度量问题,也可以克服现存的几种相似度量方法中所存在的缺陷,而且还非常适合于语言变量之间的相似度量,为IFSs在数据库的模糊查询的应用提供了一种新的方法.

Intuitionistie fuzzy set is the generalization of fuzzy set. After investigating several kinds of existent similarity measures,a new kind of＇similarity measure based on normal distribution functions is presented. Compared with the existing methods ,the proposed similarity measure is more reasonable and suited to any special situations. Moreover,this method is more reliable than which proposed by Wen-Liang Hung （2004） in applications with linguistic variables. It brings forth a brand-new method to deal with fuzzy information.