Hybrid clustering algorithm based on artificial bee colony and K-means algorithm
一种结合人工蜂群和K-均值的混合聚类算法

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.