Atmani Baghdad, Benbelkacem Sofia and Benamina Mohamed, University of Oran, Algeria

The treatment of complex systems often requires the manipulation of vague, imprecise and uncertain information. Indeed, the human being is competent in handling of such systems in a natural way. Instead of thinking in mathematical terms, humans describes the behavior of the system by language proposals. In order to represent this type of information, Zadeh proposed to model the mechanism of human thought by approximate reasoning based on linguistic variables. He introduced the theory of fuzzy sets in 1965, which provides an interface between language and digital worlds. In this paper, we propose a Boolean modeling of the fuzzy reasoning that we baptized Fuzzy-BML and uses the characteristics of induction graph classification. Fuzzy-BML is the process by which the retrieval phase of a CBR is modelled not in the conventional form of mathematical equations, but in the form of a database with membership functions of fuzzy rules.

Automatic Learning, Fuzzy Logic, Boolean Modelling, CBR, Induction graph.