Rough Set Knowledge Reduction Approach Based on Improving Genetic Algorithm

被引:0
|
作者
Yan Feng [1 ,2 ]
Gui Weihua [1 ]
Chen Yong [1 ]
Xie Yongfang [1 ]
Ren Huifeng [1 ]
机构
[1] Cent South Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China
[2] Changsha Engn & Res Inst Ltd Nonferrous Met, CHALIECO, Changsha 410011, Hunan, Peoples R China
关键词
Rough Set; Genetic Algorithm; Support Degree; Importance Degree; dissimilarity Degree;
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 this paper, a kind of rough set knowledge reduction algorithm based on improving genetic algorithm is proposed by analyzing rough sets reduction. Support degree and importance degree of condition attribute on decision attribute in information system are as heuristic information in Genetic Algorithm. On the basic of that, the GA was improved by population and individual dissimilarity degree in order to enhanced system global optimization and accelerate the convergence rate. The Practical results show that the approach is time-saving and effective for solving knowledge reduction.
引用
收藏
页码:1967 / 1971
页数:5
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