Weighted fuzzy ridge regression analysis with crisp inputs and triangular fuzzy outputs

Abstract

In this paper a new weighted fuzzy ridge regression method for a given set of crisp input and asymmetrical triangular fuzzy output values is proposed. In this approach the non-linear regression function is obtained by mapping the input samples into a higher dimensional feature space via a kernel function and constructing a linear regression estimation function in it. The method has the advantage that the solution is obtained by solving a system of linear equations. For the illustration of the proposed method a number of examples of importance are considered and the results obtained are compared with that of other methods. The results clearly demonstrate the effectiveness of our proposed method.