A new genetic algorithm for nonlinear multiregressions based on generalized Choquet integrals

Zhenyuan Wang, Hai-Feng Guo
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引用次数: 43

Abstract

This paper gives a new genetic algorithm for nonlinear multiregression based on generalized Choquet integrals with respect to signed fuzzy measures. Unlike the previous work where the values of the signed fuzzy measure are determined by random search in a genetic algorithm with other regression coefficients together; in this new algorithm, they are determined algebraically and, therefore, its complexity is much lower than before.
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基于广义Choquet积分的非线性多元回归遗传算法
本文提出了一种新的基于广义Choquet积分的非线性多元回归遗传算法。与以往的工作不同,在遗传算法中,带符号模糊测度的值是由其他回归系数一起随机搜索确定的;在新算法中,它们是代数确定的,因此其复杂度大大降低。
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