A quantum particle swarm optimization used for spatial clustering with obstacles constraints - Details

author：

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

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Abstract：

In　this　paper,　a　more　effective　Quantum　Particle　Swarm　Optimization　(QPSO)　method　for　Spatial　Clustering　with　Obstacles　Constraints　(SCOC)　is　presented.　In　the　process　of　doing　so,　we　first　proposed　a　novel　Spatial　Obstructed　Distance　using　QPSO　based　on　Grid　model　(QPGSOD)　to　obtain　obstructed　distance,　and　then　we　developed　a　new　QPKSCOC　based　on　QPSO　and　K-Medoids　to　cluster　spatial　data　with　obstacles　constraints.　The　contrastive　experiments　show　that　QPGSOD　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;　and　it　performs　better　than　Improved　K-Medoids　SCOC　(IKSCOC)　in　terms　of　quantization　error　and　has　higher　constringency　speed　than　Genetic　K-Medoids　SCOC.　©　2009　Springer　Berlin　Heidelberg.

Keyword：

Obstacles constraints; Quantum particle swarm optimization; Spatial clustering; Spatial obstructed distance

Community：

[ 1 ] [Zhang, X.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450052, China
[ 2 ] [Zhang, X.]Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou University, Fuzhou 350002, China
[ 3 ] [Wang, J.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450052, China
[ 4 ] [Wang, J.]School of Surveying and Mapping, PLA Information Engineering University, Zhengzhou 450052, China
[ 5 ] [Du, H.]School of Computer Science and Engineering, Beihang University, Beijing 100191, China
[ 6 ] [Yang, T.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450052, China
[ 7 ] [Liu, Y.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450052, China

Reprint 's Address：

[Zhang, X.]School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450052, China

Email：

zhang_xpcn@yahoo.com.cn

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Source ：

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISSN： 0302-9743

Year： 2009

Volume： 5755 LNAI

Page： 424-433

Language： English

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JCR@2005

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SCOPUS Cited Count： 2

ESI Highly Cited Papers on the List： 0 Unfold All

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30 Days PV： 1

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