Extension Clustering Algorithm and Its Applications

To overcome the shortages of traditional clustering algorithms, a clustering algorithm based on extenics was proposed. First, the algorithms build the matter-element model of sample, calculate its correlation degree and then confirm the cluster for each sample. Through the experiments of UCI data clustering and Hydraulic system fault diagnosis, we proved that the suggested algorithm can solve the clustering problem effectively, an it is more practical for data clustering.