This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the Lagrangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the cross validation procedure for selecting the optimal value of the smoothing parameter is fuzzified to fit the presented model. Some simulation experiments are then presented which indicate the performance of the proposed method.
AUTHOR KEYWORDS: Fuzzy nonparametric regression; Fuzzy regression; Local linear smoothing; Ridge estimation
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