A table lookup scheme for fuzzy logic based model identification applied to time series prediction
K. Shahida, Ibraheem, Moinuddin, M. Farooq · 2003
Zadeh introduced Fuzzy SetS in 1965 to ConcePfl). In this paper, we consider fuzzy modeling to be represent and manipulate data and information that possess an approach to form a system model using a description nonstatistical uncertain@ Since this date, fizzy logic has been applied to many fields such as indushy, medicine, language based On firzzy logic with predicates. We economics and so on, The reason for this growth in the fuzzy as a linguistic ,he use o,fizq logic tharfuuy ,ogjc provides scheme by which we linguistically behavior using a natural an appropriate mechanism to descec and/or language F21. The 'Odeling is a wem description dynamic behavior of complex physical systems that are with fuzzy quantities. quantities are expressed in d$alt to yield their conventional mathematical models. terms Of fuzzy numbers Or fuzzy associated with we can a fuzzy set as a fuu~ model of human linguistic labels. Therefore, the relation between input and concept. In this paper, we consider fuw modeling as an Output variables can be viewed as a set of fuzzy logical rules approac. to fOm a system mode/ using a description or fuzzy-set associations. Since functional variables are