The utilization of levelled fuzzy logic for more precision results

Abstract

Abstract The use of Fuzzy logic in the forecasting process, problem analysis, and decision making of the process is often used. The development of this fuzzy logic by widening the foot of the membership function as interval fuzzy type 2, fuzzy signature or carried out a hybrid between fuzzy logic and other artificial intelligence systems or a hybrid algorithm has also got quite good results. At this time, a multilevel fuzzy logic method is proposed. This multilevel Fuzzy Logic is interesting behind the input of a process in fuzzy logic, which is the output of the previous fuzzy logic or the output of a fuzzy logic analysis is input into the next stage of fuzzy logic. This multilevel fuzzy logic can be done up to several levels of depth according to the variables to be analysed. If the final analysis has the equation X(i) + Y(i) = Z(i), then the value of X (i) can be the result of A(i-1), where A(i-1) is the result of the Fuzzy Logic B(i-1) + C(i-1). by performing multilevel fuzzy logic is expected to have the value of forecasting errors or problem analysis and decision making better and more precise.