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采用一种新的跳跃基因遗传算法对获取的初始模糊系统参数进行优化。在此基础上,综合考虑隶属度函数的距离相似性和形状相似性,依据隶属度函数相似性对模糊变量的隶属度函数集进行简化。
A new hop gene genetic algorithm was used to optimize the initial fuzzy system parameters obtained. Based on this, the distance similarity and shape similarity of the membership function are comprehensively considered, and the membership function of fuzzy variables is simplified according to the similarity of membership functions.