Application Of Fuzzy Rough Set Model Based On Fuzzy ??Neighborhood Operator In Multi-criteria Decision-making

The research focus of this thesis is to use a fuzzy rough set model based on fuzzy ?-neighborhood operators and traditional decision-making ideas to establish ranking decision methods on real-valued information systems and Wu-Leung multi-scale information systems.The specific research contents are as follows:(1)A new reflexive fuzzy ?-neighborhood operator is proposed by improving the non-reflexive fuzzy neighborhood operator proposed by Ma.At the same time,the operator is used to construct a new fuzzy rough set model and the related properties are studied.Then,based on the real-valued information system,using the basic idea of PROMETHEE method,combined with the subtraction of intuitionistic fuzzy number,sorting function and intimacy coefficient to construct three different sorting decision-making schemes.Finally,the numerical analysis,comparative analysis,Spearman rank correlation analysis and experimental analysis illustrate the effectiveness and superiority of the three ranking decision-making schemes.(2)From the perspective of multi-expert group decision-making,combines the ideas of TOPSIS and COPRAS methods to propose a group decision-making method on Wu-Leung multi-scale information system.Then,two numerical examples that can constitute a multi-expert group decision-making information system and a Wu-Leung multi-scale information system are used to test the validity of the method.The comparative analysis and experimental analysis are used to illustrate the superiority of the method.Finally,the connection between group decision-making on Wu-Leung multi-scale information systems and multi-expert group decision-making is discussed from four perspectives.