Spatial Clustering in the Presence of Obstacles
Proceedings of the 17th International Conference on Data Engineering
Gene Clustering Using Self-Organizing Maps and Particle Swarm Optimization
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Clustering Spatial Data when Facing Physical Constraints
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
A Novel Spatial Clustering with Obstacles Constraints Based on Genetic Algorithms and K-Medoids
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 01
DBRS: a density-based spatial clustering method with random sampling
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
A review on particle swarm optimization algorithms and their applications to data clustering
Artificial Intelligence Review
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Spatial clustering is an important research topic in Spatial Data Mining (SDM). Although many methods have been proposed in the literature, very few have taken into account constraints that may be present in the data or constraints on the clustering. These constraints have significant influence on the results of the clustering process of large spatial data. In this paper, we propose a particle swarm optimization (PSO) method for solving Spatial Clustering with Obstacles Constraints (SCOC). We first use the PSO algorithm based MAKLINK graph to obtain the best obstructed path and then propose a novel PSO and K-Medoids method for SCOC, which is called PKSCOC, to cluster spatial data with obstacles constraints. The PKSCOC algorithm 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. The experimental results show that the PKSCOC algorithm is better than Improved K-Medoids SCOC (IKSCOC) in terms of quantization error and has higher convergence speed than Genetic K-Medoids SCOC (GKSCOC).