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Volumn 1, Issue , 2009, Pages 757-761

Combining K-means and particle swarm optimization for dynamic data clustering problems

Author keywords

Data clustering; Dynamic clustering; K means; Particle swarm optimization

Indexed keywords

CLUSTERING PROCESS; CLUSTERING RESULTS; DATA CLUSTERING; DATA SETS; DYNAMIC CLUSTERING; DYNAMIC DATA; EFFECTIVE ALGORITHMS; K-MEANS; K-MEANS METHOD; NUMBER OF CLUSTERS; OPTIMAL NUMBER; SOFTWARE SYSTEMS;

EID: 77949574485     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICICISYS.2009.5358020     Document Type: Conference Paper
Times cited : (38)

References (15)
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    • Tseng, L.Y.1
  • 9
    • 0033715579 scopus 로고    scopus 로고
    • Genetic algorithm-based clustering technique
    • U. Maulik and S. Bandyopadhyay, "Genetic algorithm-based clustering technique." Pattern Recognition vol. 33, pp.1455-1465, 2000.
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    • Maulik, U.1    Bandyopadhyay, S.2
  • 10
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    • Genetic Clustering for Automatic Evolution of Clusters and Application to Image Classification
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    • M. G. H. Omran, A. P. Engelbrecht and A. Salman, "Dynamic Clustering using Particle Swarm Optimization with Application in Unsupervised Image Classification.", TRANSACTIONS ON ENGINEERING, COMPUTING AND TECHNOLOGY, 9,199-204, 2005.
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  • 13
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    • Combinatorial particle swarm optimization (CPSO) for partitional clustering problem
    • B. Jarboui, M. Cheikh, P. Siarry and A. Rebai, "Combinatorial particle swarm optimization (CPSO) for partitional clustering problem.", Applied Mathematics and Computation, vol. 192, pp. 337-345, 2007.
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  • 15


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.