Research on Float-Coded Genetic Algorithm Based on Wavelet Denoising Mutation

Mingyi Cui, Yanli Shangguan
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引用次数: 9

Abstract

Coding is a difficult subject of research on genetic algorithm (GA). In many codes, float code (FC) is super to other codes in use. But, noise and its influence on GA performance were ignored by researches in genetic operation. Mutation played an important role of improving GA performance. Hence, float-coded genetic algorithm (FCGA) based on wavelet denoising mutation (FCGAWM) was proposed in this paper. Decomposing of FC noise was shown with wavelet in theory. FC denoising mutation was implemented in it. The experiment was made in it. The results of the research and the experiment indicated that the theory was credible and the method was feasible in it. FCGAWM is of active significance to extend application space of FCGA.
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基于小波去噪突变的浮点编码遗传算法研究
编码是遗传算法研究的一个难点。在许多代码中,浮点码(FC)优于其他正在使用的代码。但是,遗传操作研究忽略了噪声及其对遗传算法性能的影响。突变对遗传算法性能的提高起着重要作用。为此,本文提出了基于小波去噪突变的浮点编码遗传算法(FCGA)。从理论上说明了小波对FC噪声的分解。在此基础上实现了FC去噪突变。实验是在里面进行的。研究和实验结果表明,该理论是可信的,方法是可行的。fcgwan对扩展FCGA的应用空间具有积极的意义。
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