On some classes of fuzzy information granularity and their representations

This paper describes some classes of fuzzy information granularity and their representation methods. Fuzzy information granularity introduced by Zadeh is that “granularity relates to clumpiness of structure, while granulation refers to partitioning an object into a collection of granules, with a granule being a clump of objects (points) drawn together by indistinguishability, similarity, proximity, or functionality.” In this paper we show three classes of granularity structures, which are called Kleene class, Lukasiewicz class and probabilistic like class. Their meaning and representation methods are discussed. Their examples are also demonstrated. This paper would be a basis to research on the representation of fuzzy information granularity