Title of article :
LS-SVM Method for Fuzzy Nonlinear Regression
Author/Authors :
Teksen, Ümran M. Selcuk University - Faculty of Science - Department of Statistics, Turkiye , Genç, Asır Selcuk University - Faculty of Science - Department of Statistics, Turkiye
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.
Keywords :
Fuzzy Nonlineer Regression , Least Squares Support Vector Machine
Journal title :
Selcuk Journal of Applied Mathematics
Journal title :
Selcuk Journal of Applied Mathematics
