Improved Fuzzy Genetic Algorithm Applies And Research In Medical

Nowadays, the health problems has became a hot problem concerned by all world of people, combine computer technology with medicine and using intelligent algorithms can improve the speed and accuracy of disease diagnosis. So the computer system of medical diagnosis has become a research hotspot of the computer technology apply in medical. In this paper,for the deficiency of the existing research methods and the actual situation of medical diagnosis, proposed a genetic algorithm of improved fuzzy controller based on fuzzy integral, after analysis of research background and research the status quo of fuzzy controller and genetic algorithm, and study the apply in medical diagnosis system.In this paper based on the analysis of basic principles and characteristics about genetic algorithm, fuzzy controller and fuzzy integral, proposed putting forward the individual difference extent, the difference extent of individual's fitness and the difference extent of population lifetime through fuzzification as input variable of fuzzy controller, then obtained the value of evaluation by fuzzy integral, and matched the corresponding table of fuzzy variable, and take out a number in the corresponding interval as cross rate and mutation rate of next generation, then dynamic control cross rate and mutation rate of genetic algorithms, solve the problem of efficiency is low, population lack diversity and early maturity in genetic algorithm. The experiment shows that the performance of genetic algorithm improves significant through control cross rate and mutation rate dynamic.The genetic algorithm of improved fuzzy controller based on fuzzy integral proposed in this paper application in medical diagnosis system is a new application. The parameters of genetic algorithm would design targeted for the characterized of medical system and give detail coding scheme for disease patterns, specific diseases and specific symptom, and give weight of specific symptom in specific diseases and correlation coefficient between specific diseases and specific symptom by expert, The expert system realized some function including basic diseases query, diagnosis, comments feedback and raised doubts, disease information management and user management etc. in this paper the concrete realization interface of disease management is given and imitate diagnose process, then giving evaluation of this diagnose after diagnose. The experiment of this system shows that the algorithm proposed in this paper have relatively high reliability in disease diagnose.