A Novel Spatial Clustering with Obstacles Constraints Based on PNPSO and K-Medoids
نویسندگان
چکیده
In this paper, we propose a novel Spatial Clustering with Obstacles Constraints (SCOC) based on Dynamic Piecewise Linear Chaotic Map and Dynamic Nonlinear Particle Swarm Optimization (PNPSO) and K-Medoids, which is called PNPKSCOC. The contrastive experiments show that PNPKSCOC is effective and has better practicalities, and it performs better than PSO K-Medoids SCOC in terms of quantization error and has higher constringency speed than Genetic K-Medoids SCOC.
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