The Study For Pattern Recognition Based On Fuzzy Measures And Fuzzy Reasoning Algorithms

People often encounter a variety of pattern recognition problems in everyday life.For example,fingerprint unlocking,face recognition,medical diagnosis and so on.So far,many scholars have used distance measures and fuzzy reasoning algorithms to solve the problem of pattern recognition.This paper mainly studies the problem of pattern recognition based on fuzzy measures and fuzzy inference algorithms.The specific research contents are as follows:(1)A distance measure between fuzzy sets is constructed,and the algorithm for pattern recognition is given.Then a series of examples of pattern recognition are given,it is proved that the distance measure is reasonable.(2)A new distance measure between intuitionistic fuzzy sets is given.And we compare and analyze some of the extant distance measures and the new distance measure by numerical example and medical diagnosis,it is proved that the new distance measure is reasonable and can be used more accurately to solve pattern recognition problems.(3)Based on the similarity measure between fuzzy sets,a new fuzzy inference algorithm is given,we discuss the reducibility of the algorithm and investigate the robustness of fuzzy reasoning algorithm.Moreover,we use the algorithm to solve the problems of medical diagnosis.(4)A new definition of similarity measure between intuitionistic fuzzy sets is given.Based on this definition,a similarity measure is given.Moreover,a new fuzzy inference algorithm is given.Based on the algorithm,we give the medical diagnosis algorithm and use it to solve the problems of medical diagnosis.