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基于变异精密搜索的蜂群聚类算法

DOI: 10.13195/j.kzyjc.2013.0101, PP. 838-842

Keywords: 聚类,粗糙集,人工蜂群,K-means,变异算子

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Abstract:

针对K-means聚类算法过度依赖初始聚类中心、局部收敛、稳定性差等问题,提出一种基于变异精密搜索的蜂群聚类算法.该算法利用密度和距离初始化蜂群,并根据引领蜂的适应度和密度求解跟随蜂的选择概率P;然后通过变异精密搜索法产生的新解来更新侦查蜂,以避免陷入局部最优;最后结合蜂群与粗糙集来优化K-means.实验结果表明,该算法不仅能有效抑制局部收敛、减少对初始聚类中心的依赖,而且准确率和稳定性均有较大的提高.

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