Application Implementation of K-means Algorithm Based on Wolf Pack Algorithm
Xiaowei Xu, Ying Li · 2022 2nd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS) · 2022
K-means in non-hierarchical clustering analysis has become the most commonly used clustering algorithm because of its simple implementation and fast convergence speed. However, different selection of clustering center will greatly affect the clustering effect of k-means. If the clustering center is selected randomly, the algorithm will easily fall into the local optimal value and fail to achieve the optimal effect. Therefore, the uncertainty of initial clustering centers makes k-means algorithm lack of good stability. Thus, a K-means algorithm based on AEWPA (KAEWPA) is proposed in this paper to enhance the stability of clustering.