Title: Weighted fuzzy ridge regression analysis with crisp inputs and triangular fuzzy outputs
Authors: S. Balasundaram, Kapil
Addresses: School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi 110067, India. ' School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi 110067, India
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.
Keywords: fuzzy regression; learning; ridge estimation; triangular fuzzy numbers; weighted fuzzy arithmetic; crisp input; nonlinear regression.
International Journal of Advanced Intelligence Paradigms, 2011 Vol.3 No.1, pp.67 - 81
Published online: 30 Sep 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article