YAPAY SYNYR A?LARI YAKLA?IMI YLE TAHTAKÖPRÜ BARAJINDAKY AYLIK BUHARLA?MA TAHMYNY

THE ESTIMATION OF THE AMOUNT OF THE MONTHLY VAPORATION AT THE DAM OF TAHTAKÖPRÜ WITH THE APPROACH OF THE ARTIFICIAL NEURAL NETWORKS

Fatih Üneş, HAKAN VARÇİN, Kazım Kadir Dindar

Dergi: Engineering Sciences
Sayı: 2011 · Cilt: 6 Sayı: 1
Sayfa: 114–125
DOI: —

Özet

Bu çaly?mada, Tahtaköprü barajyndaki aylyk buharla?ma miktarynyn tahmini, Yapay Sinir A?lary (YSA) metodu kullanylarak ara?tyrylmy?tyr. Bu sonuçlara göre; baraj haznesi aylyk buharla?ma miktarynyn tahmininde YSA model çözüm sonuçlary, geçmi?te kullanylan klasik yöntemlerle kyyaslandy?ynda daha iyi bir yakla?ym vermi?tir.

Abstract

In this study the estimation of the amount of the monthly evaporation is investigated by the method of Articifial Neural Networks (ANN). According to these results; the analytical results of ANN model have given a better approach as compared to the classical methods that are used in the past on the amount of the monthly evaporation of the dam's reservoir.

Anahtar kelimeler: Yapay Sinir A?lary (YSA), Baraj haznesi, Buharla?ma, Çoklu-Lineer Regresyon (MLR), Otoregresif Model (AR(p),