Least Squares Support Vector Fuzzy Regression

Abstract

A least squares support vector fuzzy regression model (LS_SVFR) is proposed to estimate uncertain and imprecise data by applying the fuzzy sets principle in weight vector. Determining the weight vector and the bias term of this model requires only a set of linear equations, as against the solution of a complicated quadratic programming problem in existing support vector fuzzy regression model. Numerical example is given to demonstrate the effectiveness and applicability of the proposed model.