Granular Fuzzy State Machines, A New Modeling Methods

Fuzzy knowledge granularity (K.G.) is concluded from Zadeh investigations in fuzzy logic and system theory (L.A. Zadeh, 1973). Fuzzy logic was introduced in the 70 decade (L.A. Zadeh, 1997). This area of research has still not known completely and needed further researches and studies. Fuzzy logic is inspired from human inference and reasoning, and tried to model a complex problem as human do. In this article we introduce a new modeling method that uses K.G. to make fuzzy state machine. At first we describe some of K.G. properties that have pivotal roles in our approach. Afterwards, at second section it presents how fuzzy state machines can be used for environment modeling. Then we introduce our modeling method named, granular fuzzy state machine (GFSM). Finally in the experimental results section the compression of GFSM and Sugeno-Yasokawa modeling method is prepared