A Data Clustering Algorithm Based on Mussels Wandering Optimization

被引:0
|
作者
Yan, Peng [1 ]
Liu, ShiYao [1 ]
Kang, Qi [1 ]
Huang, BingYao [2 ]
Zhou, MengChu [3 ]
机构
[1] Tongji Univ, Dept Control Sci & Engn, Shanghai 201804, Peoples R China
[2] Rowan Univ, Dept Elect & Comp Engn, Glassboro, NJ 08028 USA
[3] New Jersey Inst Technol, Dept Elect & Comp Engn, Newark, NJ 07102 USA
基金
中国国家自然科学基金;
关键词
clustering; data mining; mussels wandering optimization; optimization; swarm intelligence;
D O I
暂无
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
As an unsupervised learning method, clustering methods plays an important role in quality data mining and various other applications. This work investigates them based on swarm intelligence, introduces a new intelligence algorithm called mussels wandering optimization (MWO) to the data clustering field, and proposes a new clustering algorithm by combining K-means clustering method and MWO. Tests on six standard data sets are performed. The results demonstrate the validity and superiority of the proposed method over some representative clustering ones.
引用
收藏
页码:713 / 718
页数:6
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