An IACO and HPSO Method for Spatial Clustering with Obstacles Constraints

Authors:
Xueping Zhang;Jiayao Wang;Dexian Zhang;Zhongshan Fan
Affiliations:
School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China 450052;School of Surveying and Mapping, PLA Information Engineering University, Zhengzhou, China 450052;School of Information Science and Engineering, Henan University of Technology, Zhengzhou, China 450052;Henan Academy of Traffic Science and Technology, Zhengzhou, China 450052
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Year:
2008

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Abstract

In this paper, we propose an Improved Ant Colony Optimization (IACO) and Hybrid Particle Swarm Optimization (HPSO) method for Spatial Clustering with Obstacles Constraints (SCOC). In the process of doing so, we first use IACO to obtain the shortest obstructed distance, and then we develop a novel HPKSCOC based on HPSO and K-Medoids to cluster spatial data with obstacles. The experimental results demonstrate that the proposed method, performs better than Improved K-Medoids SCOC in terms of quantization error and has higher constringency speed than Genetic K-Medoids SCOC.