Rough Set Knowledge Reduction Algorithm based on Chaos Genetic Algorithm

被引：0

作者：

Pan Wei ^{[1
]}

Zhu Wenliang ^{[1
]}

Liu Sili ^{[1
]}

机构：

[1] Shenyang Artillery Acad, Elect Detect Dept, Shenyang 110867, Peoples R China

来源：

2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2015年

关键词：

rough set; knowledge reduction; chaos genetic algorithm; crossover probability; mutation probability;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to obtain a valid property smallest relative reduction, this article proposed a sort of rough set knowledge reduction algorithm based on chaos genetic algorithm. The algorithm loads the chaotic variable in population genetic algorithm, making minor disturbances to progeny groups with chaos variables and adjusting perturbation amplitude gradually in the searching process to make the new algorithms not only enhancing the local search capability but also maintain the characteristics of the global optimization algorithm. At last verified by one classic example, it achieved good results whether in accuracy of reduction or in average run algebra.

引用

页码：1382 / 1387

页数：6

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