Abstract: The clustering structural analysis of fuzzy proximity relations was presented based on the granular space, and the clustering structural characteristics was discussed. Firstly, the representation and generation algorithm of the granu- lar space (or clustering structure) was given and the concept of key point sequence was introduced. The minimum dy- namic connected graph was built to explain the generation process of the granular space. Secondly, by introducing the concepts of the isomorphism and。一similarity, the corresponding determinant theorem that two fuzzy proximity relations arc isomorphic or。一similar was given. Finally, by introducing the concept of the strong。一similarity, the relationship be- twecn the isomorphism and strong。一similarity of two fuzzy proximity relations was studied. I}hesc results provide re- search tools for the general analysis of clustering structure.

Key words: Granular computing,Fuzzy proximity rclation,Granular spacc,Clustcring structure