A new identification method for use in nonlinear prediction
Felipe Montoya, Aldo Z. Cipriano, María Ramos · Journal of Intelligent & Fuzzy Systems · 2001
This paper presents a new identification method for fuzzy models used in nonlinear prediction. The structure and parameters of the fuzzy model are obtained, using input-output data, by minimization of the prediction error. The predictive capacity of the fuzzy model is compared with other linear and non-linear models analyzing an illustrative example. The results show that the new method presents a better behavior.