Genetic clustering as a parallel algorithm for approximating basins of attraction

被引：0
|
作者：
Adamska, K [1 ]
机构：
[1] Jagiellonian Univ, Inst Informatki, PL-30072 Krakow, Poland
来源：
PARALLEL PROCESSING AND APPLIED MATHEMATICS | 2004年 / 3019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：
Genetic clustering consists in performing the analysis genetic optimization results using a clustering technique to get approximations of central parts of attractor of a multimodal objective. This work presents how outputs of Hierarchical Genetic Strategy can be clustered with EM algorithm. The approach gives an opportunity of theoretical analysis aimed on evaluating of approximation accuracy. In considered case genetic clustering can be easily implemented in parallel.
引用
收藏
页码：536 / 543
页数：8
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