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
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;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.219
