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A Hybrid Monkey Search Algorithm for Clustering Analysis
Joint Authors
Zhou, Yongquan
Chen, Xin
Luo, Qifang
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-04
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Clustering is a popular data analysis and data mining technique.
The k -means clustering algorithm is one of the most commonly used methods.
However, it highly depends on the initial solution and is easy to fall into local optimum solution.
In view of the disadvantages of the k -means method, this paper proposed a hybrid monkey algorithm based on search operator of artificial bee colony algorithm for clustering analysis and experiment on synthetic and real life datasets to show that the algorithm has a good performance than that of the basic monkey algorithm for clustering analysis.
American Psychological Association (APA)
Chen, Xin& Zhou, Yongquan& Luo, Qifang. 2014. A Hybrid Monkey Search Algorithm for Clustering Analysis. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-16.
https://search.emarefa.net/detail/BIM-1051672
Modern Language Association (MLA)
Chen, Xin…[et al.]. A Hybrid Monkey Search Algorithm for Clustering Analysis. The Scientific World Journal No. 2014 (2014), pp.1-16.
https://search.emarefa.net/detail/BIM-1051672
American Medical Association (AMA)
Chen, Xin& Zhou, Yongquan& Luo, Qifang. A Hybrid Monkey Search Algorithm for Clustering Analysis. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-16.
https://search.emarefa.net/detail/BIM-1051672
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1051672