FORECASTING OF TURKEY’S ELECTRICITY CONSUMPTION USING SUPPORT VECTOR REGRESSION TRAINED WITH GENETIC ALGORITHM

Yıl 2016, Cilt: 66 Sayı: 2, 45 - 60, 01.12.2016

Oğuz Kaynar , A. Gürkan Yüksek , Ferhan Demirkoparan

https://doi.org/10.26560/iuifm.331689

Cited By: 1

Öz

Energy is a very important factor in terms of sustaining the economic
development for developing and industrialized countries. Electricity is one
of the most important forms of energy for industrialization and improvement
of living standards. The estimation and modeling of electricity consumption
has a special importance in Turkey which is a foreign-dependent country
in energy. In this study a forecasting application is made by using Turkey’s
electricity consumption, population, import, export and gross domestic
product between 1975-2014, employing support vector regression method.
By using genetic algorithm to choose the parameters of SVR, the method
outperforms significantly. 

Anahtar Kelimeler

Electricity consumption, Support Vector Regression, Genetic Algorithm, Prediction

GENETİK ALGORİTMA İLE EĞİTİLMİŞ DESTEK VEKTÖR REGRESYON KULLANILARAK TÜRKİYE’NİN ELEKTRİK TÜKETİM TAHMİNİ

Öz

Enerji, gelişmekte olan ve endüstrileşen ülkeler için ekonomik kalkın-
manın sürdürülebilmesi açısından çok önemli bir faktördür. Elektrik ener-
jisi de endüstrileşme ve yaşam standardının yükseltilmesi için en önemli
enerji formlarından biridir. Enerji bakımından dışa bağımlı bir ülke olan
Türkiye’de elektrik tüketiminin modellenmesi ve tahmin edilmesi ayrı bir
öneme sahiptir. Bu çalışmada destek vektör regresyon yöntemiyle Türki-
ye’nin 1975-2014 yılları arası elektrik tüketimi, nüfusu, ithalat, ihracat ve
GSYH verileri kullanılarak bir tahmin uygulaması yapılmıştır. DVR para-
metrelerinin seçiminde genetik algoritma yardımıyla yöntem performansı
önemli ölçüde arttırılmıştır. 

Anahtar Kelimeler

Elektrik tüketimi, Destek vektör regresyon, Ge- netik algoritma, Tahmin

Kaynakça

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