Research On The Rough Set Model Of Dual Discourse Based On Fuzzy Relations

With the rapid development of artificial intelligence technology,people put forward higher requirements for data processing.The hot issue of intelligent information processing research has always been how to obtain useful information from massive data.Rough set theory is an effective method for intelligent processing of data,and it has been successfully applied in many fields.This paper mainly focuses on the problem that the dual-domain rough set model can't deal with fuzzy data.The dual-domain dual-quantization set model and dual-domain variable precision rough set model based on fuzzy relation are proposed.This model has been studied in depth,which makes the rough set theory have a wider application field and provides a theoretical basis for further revealing the application research of rough set model.The main content has the following aspects:Firstly,in the classical rough set model,variable precision rough set model,degree rough set model,two universes rough set and other basic models,this paper deeply study the two types of dual-domain models of U × V and U to V.By introducing the fuzzy relation on the dual-domain,the fuzzy order information systems are defined on U × V and U to V respectively.According to the characteristics of the two models,different dominant relationships are established on the fuzzy order information systems,and the fuzzy sequenced precision rough set models are constructed to discuss the properties.The rough entropy,combination entropy and combination granularity are introduced to measure the uncertainty of the two types of dual-domain models.The conclusions are that as the precision threshold?becomes smaller,the roughness increases monotonically,and the rough entropy of rough set increases monotonically,and as the attribute set becomes thinner,the dominant relationship classification becomes thicker,the rough entropy of knowledge increases monotonically,the combination entropy decreases monotonically,and the combination granularity increases monotonically.This paper uses specific cases to verify the model and its properties and conclusions.Secondly,this paper constructs a U-V dual-domain dual-quantization logical conjunction rough set model by introducing binary fuzzy relations into the U-V dual domain.Through in-depth study of its model structure and mathematical characteristics,a conclusion about the model and properties of the fuzzy relationship is obtained.That is,as the precision threshold?and the degree threshold kbecome smaller,the upper approximation set becomes smaller on the dual-quantization,and the lower approximation set becomes thicker.And the example is used to verify that the dual quantization rough set model has a wider application field.Thirdly,this paper propose a U × V dual-domain dual-quantization logical conjunction rough set model based on fuzzy relation by combining the U × V dual-domain fuzzy sequenced precision rough set model and the degree rough set model.Then the rough entropy is used to measure the uncertainty.It is concluded that as the precision threshold?and degree threshold k become smaller,the roughness of the rough set increases monotonically,and the rough entropy decreases monotonically.Finally,the properties and conclusion are verified by examples.Dual-domain rough set model based on fuzzy relation can effectively solve the situation that multiple domains contain fuzzy data,and the model theory has broad application prospects.