Research On Covering-Based General IF Rough Sets And Corresponding Multi-Atribute Decision-Making

This paper mainly studies IF neighborhoods,covering-based general IF rough set models and the covering-based variable precision IF rough set models.By means of IF sets and rough sets,four types of covering-based general IF rough sets and covering-based variable precision IF rough sets are defined.Based on our raised rough sets,two kinds of multi-attribute decision making methods are put forward.This paper mainly studies the following work.The first chapter mainly introduces the related content,development background and current research status of this topic,and introduces the preliminary knowledge and main research work.In the second chapter,based on four types of fuzzy neighborhood operators proposed by D’eer,we give the definitions of four types of IF neighborhood operators and study the related structural properties.Based on the four types of IF neighborhood operators,four kinds of covering-based generalized IF rough set models are obtained,and some important conclusions are obtained.On the basis of this,a multi-attribute decision-making method based on covering-based generalized IF rough set model is proposed by combining TOPSIS method.Also,the relevant examples are given.By comparing the proposed method with some existing multi-attribute methods,we find that the proposed method is effective,sensitive and robust.This means that it can be applied to a wider and complex decision-making environment.In the third chapter,the concept of covering-based variable precision IF rough sets is introduced and some important conclusions are obtained through investigating the related properties.Based on the proposed covering-based variable-precision IF rough set models,combining TOPSIS method,we propose a decision making method based on covering-based variable precision IF rough set model.By comparing with some existing multi-attribute decision-making methods,the effectiveness and advantages of our proposed method are reflected.