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  Citation Number 2
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Yapay Sinir Ağları ile Atmosferik Parametreler Kullanılarak Türkiye için Güneş Radyasyonu Modellemesi
2016
Journal:  
Çukurova Üniversitesi Mühendislik Fakültesi Dergisi
Author:  
Abstract:

Yapay sinir ağları (YSA) yöntemi, Türkiye’de (26-45ºE ve 36-42ºN) 2004-2006 dönemlerinde atmosferik parametreler olarak verilen (sıcaklık, basınç, nem, yoğuşmaya geçebilecek su miktarı ve ay) verileri kullanarak ortalama güneş radyasyonun tahmini ve modellenmesi için uygulanmıştır. Levenberg-Marquardt (LM) öğrenme algoritmaları ve logistic sigmoid transfer fonksiyonu ağ içinde kullanılmıştır. Ağı eğitmek amacıyla, Türk Devlet Meteoroloji İşleri Genel Müdürlüğü (DMİ) ve Wyoming Üniversitesi tarafından 2004'den 2006’ye kadar Türkiye'deki beş istasyon (Adana, Ankara, İstanbul, İzmir, Samsun) için alınan meteorolojik ölçümler değerleri eğitim ve test verileri olarak kullanılmıştır. 2004- 2005 yılı verileri eğitim için, 2006 yılı verileri ise test verilerini doğrulamak için kullanılmıştır. Güneş radyasyonu elde edilmiştir.

Keywords:

Solar radiation modeling for Turkey using atmospheric parameters with artificial nerve networks
2016
Author:  
Abstract:

The method of artificial nerve networks (YSA) was applied in Turkey (26-45oE and 36-42oN) in the period 2004-2006 using data given as atmospheric parameters (temperature, pressure, moisture, quantity of water that can pass to concentration and moon) for the forecast and modeling of average solar radiation. Levenberg-Marquardt (LM) learning algorithms and logistic sigmoid transfer function are used within the network. In order to train the network, the meteorological measurements received by the Turkish State Meteorological Affairs General Directorate (DMI) and the University of Wyoming for five stations in Turkey (Adana, Ankara, Istanbul, İzmir, Samsun) from 2004 to 2006 were used as training and test data. The 2004-2005 data were used for training, and the 2006 data were used for testing data. Solar radiation has been obtained.

Keywords:

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Çukurova Üniversitesi Mühendislik Fakültesi Dergisi

Field :   Mühendislik

Journal Type :   Ulusal

Metrics
Article : 1.001
Cite : 1.754
2023 Impact : 0.14
Çukurova Üniversitesi Mühendislik Fakültesi Dergisi