Generalized Fuzzy Logic with twofold fuzzy set: Learning through Neural Net and Application to Business Intelligence

Abstract

The fuzzy logic deals with incomplete, inconsistent, uncertain, vagueand undecided information with belief. Fuzzy logic with twofold fuzzy set will give more accuracy then single membership function. In this paper, fuzzy logic with twofold fuzzy sets are studied. Fuzzy neural net used learn fuzzy inference. Fuzz certainity factor (FCF) is studied to eliminate conflict between two membership functions. Sometimes decision has to be taken under risk. Fuzzy Decision set is defined with fuzzy certainty factor (FCF). Different fuzzy resoning methods are discussed. Fuzzy inference anr reasoning mrthods are given for business intelligence.