TÜRKİYE’NİN ENERJİ TALEBİNİ TAHMİN ETMEK İÇİN TULUMLULAR SÜRÜ ALGORİTMASINA DAYALI BİR UYGULAMA

Year 2021, Volume: 8 Issue: 14, 34 - 46, 30.06.2021

Murat Aslan

Abstract

Tulumlular sürü algoritması (TSA), optimizasyon problemlerini çözmek için önerilmiş olan popülasyon tabanlı bir algoritmadır. Enerji talebinin tahmini, her ülke için oldukça önemli bir konudur. Çünkü bir ülkenin ekonomisi, enerji talebinden doğrudan etkilenmektedir. Bu nedenle, yapılan bu çalışmada, Türkiye’nin gelecekteki enerji talebini tahmin etmek için TSA tabanlı doğrusal bir yaklaşım önerilmektedir. Doğrusal modelin elde edilmesi aşamasında, bir ülkenin gayri safi yurtiçi hasıla, nüfus, ithalat ve ihracat verileri modelin giriş parametreleri olarak alınmıştır. Daha sonra bu parametrelerin optimum ağırlık katsayılarını bulmak amacıyla TSA algoritması kullanılmıştır. Önerilen modelin eğitim ve test aşaması için Türkiye'nin 1979-2011 arasındaki yıllara ait olan veri seti kullanılmıştır. Doğrusal model oluşturulduktan sonra, Türkiye’nin 2012’den 2030’a kadar olacak şekilde 20 yıllık bir süre için enerji talebi, üç farklı muhtemel senaryo için tahmin edilmiştir. Daha sonra ise önerilen model ile elde edilen deneysel sonuçlar, Türkiye’nin enerji talebini için literatürde önerilmiş olan diğer algoritmaların elde ettiği deneysel sonuçlar ile karşılaştırılmıştır. Deneysel sonuçlar ve karşılaştırmalar gösterdi ki, bu çalışma kapsamında önerilen model Türkiye’nin geleceğe dönük enerji talebini tahmin etmek için rekabetçi ve güvenilir sonuçlar elde etmiştir.

Keywords

Doğrusal model, enerji talebi, tahmin, tulumlular sürüsü algoritması

AN APPLICATION BASED ON THE TUNICATE SWARM ALGORITHM FOR PREDICTION THE ENERGY DEMAND OF TURKEY

Abstract

The tunicate swarm algorithm (TSA) is a population-based swarm algorithm proposed for solving global optimization problems. The estimation of energy demand is a serious topic for policy makers. Because the economy of a country is directly affected by energy demand. On account of this, in this study we propose a TSA based linear approach for estimation the Turkey energy demand for future. Gross domestic product, population, import and export are taken as parameters for linear model. And then, TSA algorithm has used for find the optimum weight coefficients of these parameters. For training and testing phase of proposed model the data set of Turkey in 1979 to 2011 are used. After the model is created, the energy demand of Turkey for a 20-year period from 2012 to 2030 are estimated for different three scenarios. The obtained experimental result of proposed model has been compared with the state-of-art algorithms proposed for solving energy demand of Turkey in the literature. The experimental results and comparisons show that the proposed model is highly competitive and robust optimizer for estimation the energy demand of Turkey.

Keywords

Energy demand, estimation, linear model, tunicate swarm algorithm

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