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author:

Zheng, Xiao-Ming (Zheng, Xiao-Ming.) [1] | Lu, Shi-Ying (Lu, Shi-Ying.) [2] | Wang, Xiao-Dong (Wang, Xiao-Dong.) [3]

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Abstract:

This paper proposes a clustering algorithm based on Particle Swarm Optimization Algorithm with Immunity-Vaccination (IV-PSO-KMEANS). It combines Particle Swarm Optimization (PSO) algorithm and K-means for clustering. Synchronously, Immunity-vaccination and immunity-selection mechanisms of immune system are introduced into the iterative procedure, immunity-vaccination is used to direct the procedure of particle swarm and immunity-selection is applied to select from the results of vaccination. In result, the swarm is made to move towards a better direction. The experiments show that the IV-PSO-KMEANS algorithm overcomes the problem of K-means algorithm that the results are related to the initial clustering centers, and the results of clustering are steadier and better than algorithms based on PSO.

Keyword:

Iterative methods K-means clustering Particle swarm optimization (PSO) Vaccines

Community:

  • [ 1 ] [Zheng, Xiao-Ming]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350002, China
  • [ 2 ] [Lu, Shi-Ying]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350002, China
  • [ 3 ] [Wang, Xiao-Dong]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350002, China

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Source :

Journal of the University of Electronic Science and Technology of China

ISSN: 1001-0548

CN: 51-1207/TN

Year: 2007

Issue: 6

Volume: 36

Page: 1264-1267

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 1

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