Construction And Application Of Intuitionistic Fuzzy Set Similarity Model

With the continuous advancement of science and technology,the environment in which things are located has become more and more complicated,which has increased the uncertainty of information expression.Intuitionistic fuzzy set theory to the inertia of thinking a good interpretation of the description of the uncertainty of objective things,have attracted much attention since it was proposed,and it has been applied to pattern recognition,data mining,information security and other fields,has become a key research field of decision to the party.The intuitionistic fuzzy set similarity measure is intended to describe the proximity or similarity of two intuitionistic fuzzy sets.It is an important research direction in the field of intuitionistic fuzzy sets in recent years.Interval intuitionistic fuzzy sets are a major form of extension of intuitionistic fuzzy sets and have been widely used.At present,the existing similarities of intuitionistic fuzzy sets or interval-valued intuitionistic fuzzy sets have the following problems: the similarity calculation results are inconsistent with intuition,and the discrimination is not obvious when the similarity is compared,and the actual application effect is poor.Therefore,in view of the above problems,the paper proposes a new intuitionistic fuzzy set and Interval-valued intuitionistic fuzzy sets similarity by analyzing the decision information contained in the intuitionistic fuzzy set,and applies it to the actual decision-making problem of e-commerce platform personalized recommendation performance evaluation.Based on this,the main research results of this thesis include:(1)we compare the existing intuitionistic fuzzy sets similarity function and analyze the matching degree with the similarity degree definition.Secondly,we analyze the applied limitation of the characteristic of the similarity function for the hypothesis of the intuitionistic fuzzy sets and compare the size of intuitionistic fuzzy sets through score function,and then redefines the similarity property of intuitionistic fuzzy sets.Thirdly,a new intuitionistic fuzzy sets similarity measure is designed according to the redefined similarity measure property.Finally,through the case analysis verify the validity of the method and the distinction between the decision results.(2)The membership relation of intuitionistic fuzzy sets doesn't match interval-valued intuitionistic fuzzy sets completely,so it is very difficult for the similarity measure model to match feature conditions perfectly.In this paper,we first utilize the score function and the exact function to describe the characteristic conditions of the interval-valued intuitionistic fuzzy set,and analyse the matching degree of the existing similarity measure models of interval intuitionistic fuzzy set with the characteristic conditions.Secondly,a new interval-valued intuitionistic fuzzy similarity measure model is proposed based on its geometric distance and center of gravity;Finally,the superiority and application value of the model are analyzed.(3)On the basis of comprehensive analysis of personalized recommendation content,conversion process and recommendation results,the key elements affecting performance improvement and coupling relationship are deeply analyzed,and the evaluation index system and evaluation model are designed.Finally,based on the similarity method proposed in this paper,the performance of personalized recommendation of e-commerce platform is evaluated.