K-Means clustering algorithm attracts increasing focus in recent years. A pending problem of K-Means clustering algorithm is that the performance is affected by the original cluster centers. In this paper the K-Means algorithm is improved by particle swarm optimization and the initial cluster centers are generated by particle swarm optimization..The experiments and comparisons with the classical K-Means algorithm indicate that the improved k-mean clustering algorithm has obvious advantages on execution time.
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