A hybrid monkey search algorithm for clustering analysis.
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 pap...
| Publicado en: | Scientific World Journal pp. 938239 - 938240 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103820494&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103820494 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103820494 NLM24772039 2012565132 10.1155/2014/938239 NLM24772039 PMC3967398 103820494 ppf: 938239 ppct: 1 formats: tig: atl: A hybrid monkey search algorithm for clustering analysis. aug: au: Chen, Xin Zhou, Yongquan Luo, Qifang affil: College of Information Science and Engineering, Guangxi University for Nationalities, Nanning Guangxi 530006, China. sug: subj: Algorithms Artificial Intelligence Cluster Analysis Data Mining Methods Computer Simulation Primates Physiology Reproducibility of Results Animal Studies ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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