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A Novel Hybrid Clustering Algorithms with Chaotic Particle Swarm Optimization ⋆

In order to overcome the premature convergence in the particle swarm optimization algorithm, dynamically chaotic perturbation is introduced to form a dynamically chaotic PSO, briefly denoted as DCPSO. To get rid of the drawbacks of simply finding the convex cluster and being sensitive to the initial partitions in k -means algorithm, a novel hybrid clustering algorithm combined with the DCPSO is proposed. The difference between the work and the existing ones is that DCPSO is firstly introduced into k -means. From the experimental results made on several data sets, we can see that the proposed clustering algorithms can get completely rid of the shortcomings in k -means algorithms.