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LS-SVM Method for Fuzzy Nonlinear Regression

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Author(s): Ümran M. Tekşen | Aşır Genç

Journal: Selçuk Journal of Applied Mathematics
ISSN 1302-7980

Volume: Statistics;
Issue: Special Issue;
Start page: 53;
Date: 2011;
Original page

Keywords: Fuzzy Nonlineer Regression | Least Squares Support Vector Machine.

ABSTRACT
In this study LS-SVM method is applied for fuzzy nonlinear regression whose input and output are fuzzy numbers. The method solves any problem of classification or regression via transforming to a quadratic problem without running into local solutions. This method is favourable owing to independent from a model. In this study, two practises are applied to linear and nonlinear data.
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