A Modification on Ridge Estimation for Fuzzy Nonparametric Regression
نویسنده
چکیده
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 crossvalidation 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.
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A MODIFICATION ON RIDGE ESTIMATION FOR FUZZY NONPARAMETRIC REGRESSION
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