In this paper, an improved k-means based clustering method (IKCM) is proposed. By refining the initial cluster centers and adjusting the number of clusters by splitting and merging procedures, it can avoid the algorithm resulting in the situation of locally optimal solution and reduce the number of clusters dependency. The IKCM has been implemented and tested. We perform experiments on KDD-99 data set. The comparison experiments with H-means+also have been conducted. The results obtained in this study are very encouraging. In refining the initial cluster centers and adjusting the number of clusters by splitting and merging procedures, it can avoid the algorithm resulting in the situation of local optimal solution and The perform experiments on KDD-99 data set. The comparison experiments with H-means + also have been conducted. The results obtained in this study are very encouraging.