RAINFALL ESTIMATION USING ARTIFICIAL NEURAL NETWORK METHOD

Abstract

Bu çalışmada, Isparta’nın aylık toplam yağış değerlerini (RMT) tahmin temek için yapay sinir ağı (YSA) modelleri geliştirilmiştir. RMT’yi tahmin etmek için Devlet Meteoroloji İşleri Genel Müdürlüğü’nden alınan Senirkent, Uluborlu, Eğirdir, Yalvaç ve Isparta istasyonlarına ait yağış verileri kullanılmıştır. Aynı zamanda, aynı girdi parametreleri kullanılarak çoklu lineer regresyon (ÇLR) modelleri geliştirilmiştir. Geliştirilen modellerin performanslarını değerlendirmek için ölçülmüş yağış değerleri ile YSA ve ÇLR modelleri karşılaştırılmıştır. Karşılaştırmalar YSA tahminleri ile ölçülmüş yağış değerleri arasında iyi bir uyuşma olduğunu göstermiştir.

Keywords

• Yağış, Yapay Sinir Ağları, Çoklu Lineer Regresyon, Isparta

YAPAY SİNİR AĞLARI METODU İLE YAĞIŞ TAHMİNİ

Abstract

In this study, artificial neural network (ANN) models were developed as a new approach to estimate monthly total rainfall (RMT) for Isparta. Rainfall data from Senirkent, Uluborlu, Eğirdir, Yalvaç and Isparta stations in Isparta, operated by the Turkish State Meteorological Service were used to estimate RMT. The various models were developed to estimate RMT using ANN method. Also, multiple linear regression models were developed using the same input parameters for rainfall estimation. The results of ANN and multiple linear regression models were compared with measured rainfall values to evaluate performance of the developed models. The comparison showed that there was a good agreement between the ANN estimations and measured rainfall values

Keywords

• Yağış, Yapay Sinir Ağları, Çoklu Lineer Regresyon, Isparta

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