Abstract

This paper presents a new method of estimating fuzzy multivariable nonlinear regression model for fuzzy input and fuzzy output data. This estimation method is obtained by constructing a fuzzy linear regression based on least squares support vector machine(LS-SVM) in a high dimensional feature space for the data set with fuzzy inputs and fuzzy output. Experimental results are then presented which indicate the performance of this algorithm.

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