Modellıng The Meteorologıcal Effects On Aır Temperature For Konya Cıty ın Turkey: The Approaches Of Quantıle Regressıon and Quantıle Regressıon Neural Networks
Küçük Resim Yok
Tarih
2013
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Selçuk Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this study, we propose the use of the quantile regression and quantile regression neural networks for the relationship between monthly air temperature and various meteorological effects. Meteorological effects and air temperature differs at different points in the conditional distribution. When applied to ten years (2000-2009) of data from Konya city, results of the quantile regression and quantile regression neural networks show that the contributions of the explanatory variables to the conditional distribution of the air temperature vary significantly. Finally, computation of conditional air temperature through both of the methods for multiple regression allows the estimation of complete density distributions that can be used for forecasting next month’s air temperature under an uncertainty framework.
Açıklama
Anahtar Kelimeler
Quantile Regression, Quantile Regression Neural Networks, Effects of Air Temperature
Kaynak
Journal of Selcuk University Natural and Applied Science
WoS Q Değeri
Scopus Q Değeri
Cilt
2
Sayı
1
Künye
Altindag, I., Pehlivan, N. Y. (2013).Modellıng The Meteorologıcal Effects On Aır Temperature For Konya Cıty ın Turkey: The Approaches Of Quantıle Regressıon and Quantıle Regressıon Neural Networks. Journal of Selcuk University Natural and Applied Science, 2, (1), 28-43.
