Weighted fuzzy ridge regression analysis with crisp inputs and triangular fuzzy outputs. (1st January 2011)

• Record Type: Journal Article
• Authors: Balasundaram, S.
• Is Part Of: International journal of advanced intelligence paradigms. Volume 3:Number 1(2011)
• Page Start: 67
• Page End: 81
• Publication Date: 2011-01-01
• Subjects: fuzzy regression -- learning -- ridge estimation -- triangular fuzzy numbers -- weighted fuzzy arithmetic; Artificial intelligence -- Periodicals; Machine theory -- Periodicals; Fuzzy logic -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-0386

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.