Clustering Spatial Data with Obstacles Using Improved Ant Colony Optimization and Hybrid Particle Swarm Optimization

Abstract

Spatial clustering with obstacles constraints (SCOC) has been a new topic in spatial data mining (SDM). In this paper, we propose an improved ant colony optimization (IACO) and hybrid particle swarm optimization (HPSO) method for SCOC. In the process of doing so, we first use IACO to obtain the shortest obstructed distance, which is an effective method for… (More)
DOI: 10.1109/FSKD.2008.128

Topics

2 Figures and Tables

Cite this paper

@article{Zhang2008ClusteringSD, title={Clustering Spatial Data with Obstacles Using Improved Ant Colony Optimization and Hybrid Particle Swarm Optimization}, author={Xueping Zhang and Qingzhou Zhang and Zhongshan Fan and Gaofeng Deng and Chuang Zhang}, journal={2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery}, year={2008}, volume={2}, pages={424-428} }