A hybrid algorithm for solving generalized class cover problem

被引：0
|
作者：
Huang, Yanxin [1 ]
Zhou, Chunguang
Wang, Yan
Bao, Yongli
Wu, Yin
Li, Yuxin
机构：
[1] NE Normal Univ, Inst Cytol & Genet, Changchun 130024, Peoples R China
[2] Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China
[3] NE Normal Univ, Minist Educ, Res Ctr Agr & Med Gene Engn, Changchun 130024, Peoples R China
来源：
ADVANCES IN NATURAL COMPUTATION, PT 1 | 2006年 / 4221卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A generalized class cover problem is presented in this article, and then reduced to a constrained multi-objective optimization problem. Solving this problem is significantly important to construct a robust classification system. Therefore, three algorithms for solving the generalized class cover problem are proposed, which are greedy algorithm, binary particle swarm optimization algorithm, and their hybrid algorithm. Comparison results of these three methods show that the hybrid algorithm can get better solutions in less runtime.
引用
收藏
页码：610 / 619
页数：10
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