摘要
给出一种使适合度函数参数、交叉概率和突变概率随搜索精度自适应调整的遗传算法，并以直接从输入输出数据中提取模糊规则为例与常规遗传算法进行了仿真比较，该算法明显优于常规算法。
A kind of genetic algorithm is given, in which the parameters of a fitness function, the probability of crossover and mutation change adaptivetuning with the precision of stochastic search. And the proposed method is compared with the classical genetic algorithm in the field of the extracting fuzzy rules from the inputoutput data. The simulation shows the improved genetic algorithm is more efficient than the classical method.
出处
《青岛化工学院学报（自然科学版）》
1998年第2期169-173,共5页
Journal of Qingdao Institute of Chemical Technology(Natural Science Edition)
