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Hybrid clustering algorithm based on artificial bee colony and K-means algorithm

BI Xiao-jun,GONG Ru-jiang(College of Information & Communication Engineering,Harbin Engineering University,Harbin 150001,China)  
The traditional K-means clustering algorithm is too dependent on the initial clustering centers.With regards to this,this paper proposed a mixed clustering method based on the improvement artificial colony algorithm and the K-means algorithm.The new method combined the advantages of regulating ability of global optimization and local optimization with rapid convergence of K-means clustering algorithm to improve the robustness of the algorithm.Experiments show that the clustering result of the new method is significantly improved,not only the stability.
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