Research Of Knowledge Reduction And Reasoning Method Based On Dynamic Fuzzy Linguistic Formal Context

The goal of the next-generation artificial intelligence is to use reasoning models based on experience and knowledge to mimic intelligent human behavior in the real world,and to solve problems in incomplete information,uncertain environments and dynamically changing environment.Uncertain environments has some linguistic value description of fuzzy data,some data is dynamic change.In order to process this kind of data information,this thesis puts forward a dynamic fuzzy linguistic formal context,constructs a linguistic-valued data representation model under dynamic and incomplete environments,and further studies knowledge reduction and reasoning methods in dynamic fuzzy linguistic formal context.The details of the study are as follows(1)In order to handle fuzzy linguistic data information in dynamic environment,based on dynamic fuzzy logic,dynamic fuzzy linguistic terms set is proposed and related operations are defined.The dynamic fuzzy linguistic formal context describes the relationship between object and attribute with dynamic fuzzy linguistic value.Next,we extracts the dynamic fuzzy linguistic concept,construct the dynamic fuzzy linguistic concept lattice and analyze the related properties.Through examples,we illustrate that the dynamic fuzzy linguistic concept can represent the degree of attribute change more intuitively.(2)Aiming at the problem of incomplete representation of knowledge caused by uncertainty and fuzziness in the real world,a linguistic data representation model under incomplete environment is proposed.Firstly,the formal context of incomplete dynamic fuzzy linguistic is proposed,and the approximate concept of dynamic fuzzy linguistic is extracted.Secondly,in the incomplete dynamic fuzzy linguistic formal context,other attribute values of objects and dynamic fuzzy linguistic similarity between objects and other objects are considered respectively,and the secondary completion method of incomplete formal context is investigated.Finally,the attribute reduction of dynamic fuzzy formal background is studied based on classification and reduction methods,so as to simplify the reduction process and improve the reduction efficiency.(3)To deal with the uncertainty reasoning problem in dynamic fuzzy linguistic environment,a dynamic fuzzy linguistic reasoning method is studied.Firstly,the dynamic fuzzy linguistic formal decision context is proposed,and the dynamic fuzzy linguistic decision rules are extracted through the coordination of the judgment formal context.Then,the calculation methods of dynamic fuzzy linguistic-valued similarity of rule antecedents and decision properties of unknown objects are proposed.Based on this,a dynamic fuzzy linguistic reasoning method is proposed to predict uncertain decision results.Finally,the practicality and feasibility of the method are verified by an example of disease diagnosis.