Mixed clustering algorithm with artificial fish swarm and improved K-means

被引：0
|
作者：
Yang, Hao [1 ]
机构：
[1] Zhejiang Univ Media & Commun, Coll New Media, Hangzhou, Zhejiang, Peoples R China
来源：
PROCEEDINGS OF THE 2ND INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2016) | 2016年 / 24卷
关键词：
clustering algorithm; artificial fish swarm; K-means;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In allusion to increase the speed and accuracy rate of clustering algorithm, the paper proposes mixed clustering algorithm with artificial fish swarm and improved K-means. Firstly, it leads artificial fish swarm algorithm to clustering algorithm and proposes artificial fish swarm clustering algorithm. Secondly, it improves traditional K-means algorithm and gives improved K-means algorithm. Finally, it gets mixed clustering algorithm with artificial fish swarm and K-means.
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页码：226 / 229
页数：4
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