摘要：For centuries,the natural laws have been the source of human creativity. Recently,simulation of the animal life and behavior as the algorithms have been studied in the optimization problems. In this article,an evolutionary algorithm was proposed to diagnosis a challenging disease which deals with several factors. The proposed algorithm was developed according to the honeybee reproduction cycle (HBRC) to create the fuzzy decision rules in an acute appendicitis diagnostic system. In this article thus,the useful clinical factors available in the first hours of the pain were explored and the diagnosis knowledge was discovered using an evolutionary algorithm in a Fuzzyrule based system. The optimization process in the algorithm decreases the chance of local optima in comparison with other techniques such as genetic algorithms. Experimental results showed that the proposed algorithm improves considerably the optimization performance in the diagnostic problem.
关键词：Clinical decision support systems;Genetic algorithms;Evolutionary algorithms;Acute appendicitis;Fuzzy systems.
