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author:

Zhang, X. (Zhang, X..) [1] | Wu, J. (Wu, J..) [2] | Si, H. (Si, H..) [3] | Yang, T. (Yang, T..) [4] | Liu, Y. (Liu, Y..) [5]

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Scopus

Abstract:

The paper proposed a novel Ant Colony Optimization (ACO) and Quantum Particle Swarm Optimization (QPSO) method for Spatial Clustering with Obstacles Constraints (SCOC). We first developed AQPGSOD using ACO and QPSO based on grid model to obtain obstructed distance, and then we presented a new QPKSCOC based on QPSO and K-Medoids to cluster spatial data with obstacles. The experimental results show that AQPGSOD is effective, and QPKSCOC can not only give attention to higher local constringency speed and stronger global optimum search, but also get down to the obstacles constraints and practicalities of spatial clustering. © 2009 IEEE.

Keyword:

Ant Colony Optimization; Obstacles constraints; Obstructed distance; Quantum Particle Swarm Optimization; Spatial clustering

Community:

  • [ 1 ] [Zhang, X.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China
  • [ 2 ] [Zhang, X.]Key Laboratory of Spatial Data Mining and Information, Sharing of Ministry of Education, Fuzhou University, Fuzhou, China
  • [ 3 ] [Wu, J.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China
  • [ 4 ] [Si, H.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China
  • [ 5 ] [Yang, T.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China
  • [ 6 ] [Liu, Y.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China

Reprint 's Address:

  • [Zhang, X.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China

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Source :

2009 International Conference on Artificial Intelligence and Computational Intelligence, AICI 2009

Year: 2009

Volume: 1

Page: 154-158

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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