LS-SVM method for fuzzy nonlinear regression
Yükleniyor...
Tarih
2011
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
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
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
Tekşen, Ü. M., Genç, A. (2011). LS-SVM method for fuzzy nonlinear regression. Selcuk Journal of Applied Mathematics, 53-60.
