Improved artificial bee colony clustering algorithm based on K-means

被引：1

作者：

Wang Xuemei ^{[1
]}

Wang Jin-bo ^{[2
]}

机构：

[1] Cheng Dong Coll Northeast Agr Univ, Dept Comp Sci & Technol, Harbin 150025, Peoples R China

[2] Liaoning Co Ltd China Mobile Grp, Shenyang 110000, Peoples R China

来源：

MECHATRONICS ENGINEERING, COMPUTING AND INFORMATION TECHNOLOGY | 2014年 / 556-562卷

关键词：

Artificial Bee Colony (ABC) algorithm; Cluster analysis; K-means; Nonlinear selection;

D O I：

10.4028/www.scientific.net/AMM.556-562.3852

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

According to the defects of classical k-means clustering algorithm such as sensitive to the initial clustering center selection, the poor global search ability, falling into the local optimal solution. Artificial Bee Colony algorithm based on K-means was introduced in this article, then put forward an improved Artificial Bee Colony algorithm combined with k-means clustering algorithm at the same time. The experiments showed that the method has solved algorithm stability of k-means clustering algorithm well, and more effectively improved clustering quality and property.

引用

页码：3852 / +

页数：2

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