A New Hybrid Ant Colony Algorithm for Clustering Problem

被引：3
|
作者：
Shang, Gao [1 ]
机构：
[1] Jiangsu Univ Sci & Technol, Sch Comp Sci & Engn, Zhenjiang 212003, Peoples R China
来源：
2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION WORKSHOP: IITA 2008 WORKSHOPS, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/IITA.Workshops.2008.257
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The known mathematical model for clustering problems is given in this paper. With the K-Means algorithm, the simulated annealing algorithm and a novel hybrid ant colony algorithm is integrated with the K-means algorithm to solve clustering problems. The advantages and shortages of K-Means algorithm, simulated annealing algorithm and the hybrid ant colony algorithm are then analyzed, so that effectiveness of the hybrid ant colony algorithm would be illustrated through results.
引用
收藏
页码：28 / 31
页数：4
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