DocumentCode
468360
Title
Clustering Spatial Data with Obstacles Constraints by PSO
Author
Zhang, Xueping ; Qin, Fen ; Wang, Jiayao ; Fu, Yongheng ; Chen, Jinghui
Author_Institution
Henan Univ. of Technol., Zhengzhou
Volume
3
fYear
2007
fDate
24-27 Aug. 2007
Firstpage
543
Lastpage
547
Abstract
This paper proposes a particle swarm optimization (PSO) method for solving Spatial Clustering with Obstacles Constraints (SCOC). In the process of doing so, we first use PSO to get obstructed distance, and then we developed the PSO K-Medoids SCOC (PKSCOC) to cluster spatial data with obstacles constraints. The experimental results show that PKSCOC performs better than Improved K-Medoids SCOC (IKSCOC) in terms of quantization error and has higher constringency speed than Genetic K-Medoids SCOC (GKSCOC).
Keywords
data analysis; genetic algorithms; particle swarm optimisation; pattern clustering; PSO k-medoids SCOC; genetic k-medoids SCOC; obstacles constraints; particle swarm optimization method; quantization error; spatial clustering; spatial data clustering; Bridges; Clustering algorithms; Data engineering; Genetics; Information science; Particle swarm optimization; Programmable logic arrays; Quantization; Rivers; Technology planning;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2874-8
Type
conf
DOI
10.1109/FSKD.2007.219
Filename
4406297
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