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Article: Notice of Retraction: Hybrid adaptive niche to improve particle swarm optimization clustering algorithm

TitleNotice of Retraction: Hybrid adaptive niche to improve particle swarm optimization clustering algorithm
Authors
Issue Date2011
Citation
Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011, 2011, v. 1, p. 134-138 How to Cite?
AbstractClustering is an important data analysis and data mining technique. PSO clustering is one of the popular partition algorithm. But it often suffers from the problem of premature convergence and traps in suboptimum solution. This paper uses adaptive niche particle swarm algorithm to improve clustering. And it is also studied the impact of different fitness optimization function to clustering data. The results show that the algorithm which hybrids adaptive niche to PSO clustering techniques has more competitive. It also shows that the new fitness optimization function we proposed is more promising in the fields of high dimension data set and large difference of the number samples in clusters than the popular function of Merwe introduced. © 2011 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/329820

 

DC FieldValueLanguage
dc.contributor.authorJiang, Lei-
dc.contributor.authorDing, Lixin-
dc.contributor.authorLei, Yunwen-
dc.contributor.authorChen, Ming-
dc.contributor.authorZeng, Zhigao-
dc.date.accessioned2023-08-09T03:35:34Z-
dc.date.available2023-08-09T03:35:34Z-
dc.date.issued2011-
dc.identifier.citationProceedings - 2011 7th International Conference on Natural Computation, ICNC 2011, 2011, v. 1, p. 134-138-
dc.identifier.urihttp://hdl.handle.net/10722/329820-
dc.description.abstractClustering is an important data analysis and data mining technique. PSO clustering is one of the popular partition algorithm. But it often suffers from the problem of premature convergence and traps in suboptimum solution. This paper uses adaptive niche particle swarm algorithm to improve clustering. And it is also studied the impact of different fitness optimization function to clustering data. The results show that the algorithm which hybrids adaptive niche to PSO clustering techniques has more competitive. It also shows that the new fitness optimization function we proposed is more promising in the fields of high dimension data set and large difference of the number samples in clusters than the popular function of Merwe introduced. © 2011 IEEE.-
dc.languageeng-
dc.relation.ispartofProceedings - 2011 7th International Conference on Natural Computation, ICNC 2011-
dc.titleNotice of Retraction: Hybrid adaptive niche to improve particle swarm optimization clustering algorithm-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ICNC.2011.6021907-
dc.identifier.scopuseid_2-s2.0-80053394276-
dc.identifier.volume1-
dc.identifier.spage134-
dc.identifier.epage138-

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