Applications of type-2 fuzzy logic systems to forecasting of time-series

In this paper, we begin with a type-1 fuzzy logic system (FLS), trained wit h noisy data, We then demonstrate how information about the noise in the tr aining data can be incorporated into a type-2 FLS, which can be used to obt ain bounds within which the true (noisefree) output is likely to lie. We do this with the example of a one-step predictor for the Mackey-Glass chaotic time-series [M.C, Mackey, L, Glass, Oscillation and chaos in physiological control systems, Science 197 (1977) 287-280], We also demonstrate how a ty pe-2 .FLS can be used to obtain better predictions than those obtained with a type-1 FLS, (C) 1999 Elsevier Science Inc. All rights reserved.