An Adaptive Genetic Algorithm based on Rough Set Attribute Reduction

被引：4
|
作者：
BingXiang Liu [1 ]
Feng Liu [1 ]
Xiang Cheng [1 ]
机构：
[1] JDZ Ceram Inst, Sch Informat Engn, Jingdezhen 333403, Peoples R China
来源：
2010 3RD INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS (BMEI 2010), VOLS 1-7 | 2010年
关键词：
Rough set; Genetic Algorithm; Adaptive; Attribute reduction;
D O I：
10.1109/BMEI.2010.5639635
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
Attribute reduction is one of important problem of rough set theory. In order to get effectively attribute reduction, we presented an algorithm of attribute reduction of rough set based on improved adaptive genetic algorithm (IAGA). IAGA adjusts the crossover probability and mutation probability of each individual according to individual fitness value. The optimization capability and the convergence velocity of adaptive GA are improved.
引用
收藏
页码：2880 / 2883
页数：4
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