Intuitionistic Fuzzy Set Reasoning And Its Application In The Field Of Assisted Disease Diagnosis

This paper mainly studies the rule-based fuzzy expert systems,focuses on the methods of knowledge representation and fuzzy reasoning,and applies the theoretical,using database and their relations constructs a rule-based medical auxiliary diagnosis expert system.In this thesis,research work and results are as follows:Firstly,starting from the clinical practice of medicine,it gives a detailed description of the representation of knowledge,the determination of membership functions and the establishment of fuzzy rules based on the theory of fuzzy mathematics,fuzzy inference technology,fuzzy expert system,and emphatically introduces the concept of intuitionistic fuzzy sets.This paper gives three kinds of fuzzy measures,conclude of the related measure,the distance measure and the similarity measure,are reasoned and applied in the examples in detail.Secondly,according to variety of ways to get the disease-related knowledge and disease symptom research in different degrees,using production-based representation of the knowledge into rules that meet the system requirements,according to the choice of knowledge representation and fuzzy reasoning method to establish a rules of the disease diagnosis expert system,the system's rule base integrates a lot of experts in the field of knowledge,using knowledge of the patient's symptoms to analyze and diagnose,and show the diagnosis.The experimental simulation shows that the fuzzy expert system established in this paper can automatically diagnose the common twenty-seven kinds of diseases and the system can meet the actual requirements and achieve the purpose of auxiliary diagnosis.