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作者机构:Univ Cordoba Dept Comp Sci E-14071 Cordoba Spain
出 版 物:《SOFT COMPUTING》 (Soft Comput.)
年 卷 期:2005年第9卷第4期
页 面:270-279页
核心收录:
学科分类:08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
主 题:real-coded genetic algorithms statistical features learning confidence intervals L-2-norm
摘 要:We cannot deny the effort that the scientific community is devoting to the explanation of the features of the crossover operator of real-coded genetic algorithms and its effect over the evolutive process. This paper is another step in that direction, we analyze the behaviour of the Confidence Interval Based Crossover using L-2 Norm (CIXL2). This crossover is based on the learning of the statistical features of localization and dispersion of the best individuals of the population. The crossover obtains, by means of a L-2 norm, the estimators of the parameters of localization and dispersion of the distributions of the fittest individuals. From this estimation three virtual parents are created using the localization parameter and the lower and upper bounds of the bilateral confidence intervals of the gene values of the best individuals of the population. This paper studies the statistical features of the offspring generated by this crossover and corroborates this study showing the behaviour of the crossover in a set of test functions.