A Novel Clustering Algorithm With Ant Colony Optimization

被引:0
|
作者
Fu, Hui [1 ]
机构
[1] Guangdong Polytech Normal Univ, Dept Comp Sci, Guangzhou 510665, Guangdong, Peoples R China
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
Clustering Analysis is an important area of data mining. A kind of new clustering algorithm with ant colony optimization based on cluster center initialization is proposed in this paper. The new algorithm gives initialized cluster centers by different methods, then solves clustering problems by iterated method. Three methods of cluster center initialization are used in clustering algorithm with ant colony optimization-Sacc. Three datasets-butterfly data, iris and wine are chosen for the compare of three algorithms. The results of several times experiments show that the new algorithm is less in running time, is better in clustering effect and more stable than Sacc. Experimental results validate new algorithm's efficiency.
引用
收藏
页码:1037 / 1040
页数:4
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