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- Publisher Website: 10.1109/ICNC.2011.6021907
- Scopus: eid_2-s2.0-80053394276
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Article: Notice of Retraction: Hybrid adaptive niche to improve particle swarm optimization clustering algorithm
Title | Notice of Retraction: Hybrid adaptive niche to improve particle swarm optimization clustering algorithm |
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Authors | |
Issue Date | 2011 |
Citation | Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011, 2011, v. 1, p. 134-138 How to Cite? |
Abstract | Clustering 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 Identifier | http://hdl.handle.net/10722/329820 |
DC Field | Value | Language |
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dc.contributor.author | Jiang, Lei | - |
dc.contributor.author | Ding, Lixin | - |
dc.contributor.author | Lei, Yunwen | - |
dc.contributor.author | Chen, Ming | - |
dc.contributor.author | Zeng, Zhigao | - |
dc.date.accessioned | 2023-08-09T03:35:34Z | - |
dc.date.available | 2023-08-09T03:35:34Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011, 2011, v. 1, p. 134-138 | - |
dc.identifier.uri | http://hdl.handle.net/10722/329820 | - |
dc.description.abstract | Clustering 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.language | eng | - |
dc.relation.ispartof | Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011 | - |
dc.title | Notice of Retraction: Hybrid adaptive niche to improve particle swarm optimization clustering algorithm | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/ICNC.2011.6021907 | - |
dc.identifier.scopus | eid_2-s2.0-80053394276 | - |
dc.identifier.volume | 1 | - |
dc.identifier.spage | 134 | - |
dc.identifier.epage | 138 | - |