Regularized least squares support vector fuzzy regression

For estimating fuzzy system which is imprecise and represented by fuzzy sets, a regularized least squares support vector fuzzy regression model is proposed. The proposed fuzzy regression model is applying the fuzzy sets principle in weight vector and bias term. Determining the weight vector and the bias term of the proposed fuzzy regression model only requires a single matrix inversion, as against the solution of a complicated quadratic programming problem in previous support vector fuzzy regression model. Numerical examples are given to demonstrate the effectiveness of the proposed fuzzy regression model.