融合记分函数的直觉模糊集相似度性质再定义与模型设计

Redefinition and model design of intuitionistic fuzzy sets similarity measure properties of fusion score function

相似度函数是含有直觉模糊集(intuitionistic fuzzy sets,IFS)的多准则决策的重要内容,直接影响了决策结果。通过比较现有的18种IFS的相似度函数,分析了其与相似度定义的匹配程度。其次,分析了IFS相似度部分性质应用的局限性,依据记分函数来比较直觉模糊数的大小,进而重新定义了IFS的相似度性质。再次,针对重新定义的相似度性质,设计了一种新的IFS相似度度量模型。最后,通过算例分析和灵敏度分析验证本文方法的有效性和对决策结果的区分度。

Similarity function is an important content of intuitionistic fuzzy sets（IFS）multi-criteria decision making,which directly affects the decision result.This paper compares the existing 18 kinds of IFS similarity functions and analyzes the matching degree with the similarity degree definition.Secondly,this paper analyzes the applied limitation of the characteristic of the similarity function for the hypothesis of the IFS and compares the size of IFS through the score function,and then redefines the similarity property of IFS.Thirdly,a new IFS similarity measure is designed according to the redefined similarity measure property.Finally,the case analysis and sensitivity analysis verify the validity of the method and the distinction between the decision results.