Abstract-In this paper, we present the theory and design of interval type-2 fuzzy logic systems (FLSs). We propose an efficient and simplified method to compute the input and antecedent operations for interval type-2 FLSs; one that is based on a general inference formula for them. We introduce the concept of upper and lower membership functions (MFs) and illustrate our efficient inference method for the case of Gaussian primary MFs. We also propose a method for designing an interval type-2 FLS in which we tune its parameters. Finally, we design type-2 FLSs to perform time-series forecasting when a nonstationary time-series is corrupted by additive noise where SNR is uncertain and demonstrate improved performance over type-1 FLSs. Index Terms-Interval type-2 fuzzy sets, nonsingleton fuzzy logic systems, time-series forecasting, tuning of parameters, type-2 fuzzy logic systems, upper and lower membership functions.
The authors REF present rules and ideas for Interval type-2 fuzzy logic systems.
Interval type-2 fuzzy logic systems: theory and design
IEEE Trans. Fuzzy Systems
IEEE Trans. Fuzzy Systems
Computer Science Mathematics