Time Series Prediction by Perturbed Fuzzy Model

This paper presents a fuzzy system approach to the prediction of nonlinear time series and dynamical systems based on a fuzzy model that includes its derivative information. The underlying mechanism governing the time series, expressed as a set of IF–THEN rules, is discovered by a modified structure of fuzzy system in order to capture the temporal series and its temporal derivative information. The task of predicting the future is carried out by a fuzzy predictor on the basis of the extracted rules and by the Taylor ODE solver method. We have applied the approach to the benchmark Mackey-Glass chaotic time series.

• Type: Conference
• Year: 2007
• Where: EUSFLAT
• Authors: Paulo Salgado, Getúlio Igrejas, Fernando Gouveia
• Keywords: Derivative Information, EUSFLAT 2007, Nonlinear Time Series, Time Series