基于多参数的直觉模糊集相似度及其应用

Similarity measure and its application based on multi-parametric intuitionistic fuzzy sets

有关直觉模糊集相似度的文献很多,但是现有的部分公式在处理实际问题时效果不理想。土耳其学者Boran和Akay提出了一种新的双参数相似度公式,改进了主流公式中存在的一些模式识别失灵问题。但是在他们引入隶属度、非隶属度、犹豫度取值对应等腰直角三角形的区域中,只考虑了斜边中线上的点。通过对这个公式改进,使情况一般化,并给出了一个更泛化的多参数公式,证明了其正确性,验证了其在模式识别中的有效性。

There is a lot of literature related to similarity measure of the intuitionistic fuzzy set,while some of the existing formulae are inefficient to handle practical problems.Famous scholars Boran and Akay who are from Turkey proposed a new biparametric formula about similarity measure,which improved the failure of some pattern recognitions in the mainstream method.Meanwhile,they introduced an isosceles right triangle area which is corresp-onding to the values of the membership degree,the non-membership degree and the hesitancy degree,and only points on the midline of the hypotenuse were taken into consideration.This paper improves the formula to make the condition generalization and gives a more generalized multi-parametric formula which proves its correctness and verifies its effectiveness in pattern recognition.