Research On The Information Measure Of Two Classes Of Generalized Fuzzy Sets And Their Applications

In the real world,there are a large number of fuzzy phenomena and fuzzy concepts,which make it impossible for people to give an accurate evaluation of things around them,so they can only be described by fuzzy language.The emergence of fuzzy sets theory provides a more reasonable way to describe many fuzzy phenomena in nature.Subsequently,many scholars have conducted in-depth research on fuzzy sets,and various extended forms of fuzzy sets have been proposed and applied in many fields,such as statistical decision making and pattern recognition.Hesitant fuzzy sets and neutrosophic cubic sets are two kinds of extended forms of fuzzy sets,because they describe problems more vividly,so it is of great theoretical value and practical significance to study them more deeply.The main research contents of this paper are as follows:The first chapter mainly introduces some research backgrounds and research status of fuzzy sets 、 hesitant fuzzy sets and neutrosophic cubic sets,and gives correlation preliminary knowledge.The second chapter based on the existing distance measure of hesitant fuzzy sets,the distance with deviation degree and the distance with parameter are given,and apply them in pattern recognition.The third chapter proposes the relevant definition of the neutrosophic cubic number and ELECTRE method is improved.Numerical examples are given to illustrate the superiority of the proposed method.The fourth chapter based on the correlation theory,the correlation coefficients of the neutrosophic cubic sets are proposed,and the properties of the correlation coefficients are dicussed.A numerical example is given to illustrate the effectiveness of this method.The fifth chapter is conclusion and prospect.