LS-SVM method for fuzzy nonlinear regression

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Küçük Resim

Tarih

2011

Dergi Başlığı

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Yayıncı

Selcuk University Research Center of Applied Mathematics

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

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.

Açıklama

URL: http://sjam.selcuk.edu.tr/sjam/article/view/290

Anahtar Kelimeler

Fuzzy nonlineer regression, Least squares support vector machine, Bulanık doğrusal olmayan regresyon, En küçük kareler destek vektör makinesi

Kaynak

Selcuk Journal of Applied Mathematics

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Sayı

Künye

Tekşen, Ü. M., Genç, A. (2011). LS-SVM method for fuzzy nonlinear regression. Selcuk Journal of Applied Mathematics, 53-60.