Shadowed Sets-based Rough Fuzzy Possibilistic C-means Clustering
基于阴影集的粗糙模糊可能性C均值聚类算法

It has been shown that soft clustering is advantageous over hard clustering in describing clusters without crisp boundaries. Both rough sets and fuzzy sets arc effective mathematical tools in handling uncertainty. As claimed in many studies,they are complementary. The theories of rough sets and fuzzy sets have been integrated into clustering algorithms,such as rough fuzzy possibilistic Gmeans clustering (RFPCM). In this study, we introduced the shadowed sets optimization theory and proposed an objective method to select the threshold in RFPCM.