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YAPAY SİNİR AĞLARI İLE TÜRKİYE NET ENERJİ TALEP TAHMİNİ

FORECASTING THE NET ENERGY DEMAND OF TURKEY BY ARTIFICIAL NEURAL NETWORKS

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Abstract (2. Language): 
In this study, the net energy demand of Turkey has been predicted by artificial neural networks (ANN). In order to forecast net energy demand of Turkey, Gross Domestic Product (GDP), population, import, export, area of the building and vehicles number data was used as input of ANN model. The prediction performance of built ANN model has been demonstrated in comparison with a multiple linear regression technique. The comparisons are shown the superiority of ANN. By using the model which is acceptable and high accuracy, the net energy demand of Turkey has been predicted that between the years of 2011-2025.
Abstract (Original Language): 
Bu çalışmada, yapay sinir ağları (YSA) ile Türkiye net enerji talebi tahmin edilmiştir. Türkiye net enerji talebini tahmin etmek için 1970-2010 yılları arasındaki Gayri Safi Yurtiçi Hâsıla (GSYH) , nüfus, ithalat, ihracat, bina yüz ölçümü ve taşıt sayısı değişken verileri YSA modelinin girdisi olarak kullanılmıştır. Kurulan YSA modelinin tahmin performansı, çoklu doğrusal regresyon tekniği ile karşılaştırmalı olarak ortaya konmuştur. Yapılan karşılaştırmalar, YSA’nın üstünlüğünü göstermektedir. Kabul edilebilir ve yüksek doğruluktaki YSA modeli ile 2011-2025 yılları arası Türkiye net enerji talebi tahmin edilmiştir.
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