k-means融合FCM算法聚类研究

On the Hybrid Model Combined k-means with FCM for Clustering

k-means融合FCM算法执行聚类过程,是在k-means算法完成聚类后,以其聚类结果作为FCM算法执行的初值,并通过FCM算法的执行完成。从结果分析可以看出,该算法聚类的效果比单纯使用FCM算法好,能够减少FCM算法循环体迭代运行次数并增强算法的鲁棒能力。

Combining k-means with FCM algorithm to execute clustering process refers to that we can take the results of k-means clustering algorithm as a FCM initial value to complete clustering process. As can be seen from the results, the clustering effect is better than FCM. It must reduce the number of loop iterations and enhance the robustness of the algorithm.