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Journals / El-Cezeri / 2022 / Cilt: 9 - Sayı: 3

Estimation of Net Energy Consumption for Turkey Based on Economic Factors

Türkiye İçin Ekonomik Faktörlere Bağlı Olarak Net Enerji Tüketimi Tahmini

Derya ŞENCAN
Arzu ŞENCAN ŞAHİN
Journal
El-Cezeri
Pages
1101–1111
Publication Date
2022-09-30
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results obtained, it is showing that both models can be successfully used to forecast energy consumption.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Energy, which is one of the main determinants of the economy, is an important production factor for all countries.
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Key Findings & Data:As a developing country, Turkey is a country that increases its energy demand day by day.
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Conclusion & Impact:The results obtained, it is showing that both models can be successfully used to forecast energy consumption.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Net enerji tüketimi · Sosyo-ekonomik değişkenler · Tahmin

Abstract

Energy, which is one of the main determinants of the economy, is an important production factor for all countries. As a developing country, Turkey is a country that increases its energy demand day by day. It is very important to make reliable energy consumption forecasts for the future in today's world where there is an energy crisis. In this work; the artificial neural networks (ANN) and adaptive-network-based fuzzy inference system (ANFIS) models were used to examine the effects of imports, exports, economic growth (Gross Domestic Product) and population on net energy consumption of Turkey. The reliability of the ANN and ANFIS models was determined using several statistical indicators. In the ANN model; R2, MAPE, and cov values were found as 0.997397669, 0.78259322, and 5.3228538, respectively. In the ANFIS model; R2, MAPE, and cov values were found as 0.997845364, 0.70709233, and 4.84339908, respectively. The obtained results from the ANN are compared with the ANFIS, in which the same data sets are used. The ANFIS model is a little better than ANN model. Using the weights obtained from the trained network, a new formula for determining net energy consumption is proposed. The results obtained, it is showing that both models can be successfully used to forecast energy consumption.

Özet

Ekonominin temel belirleyicilerinden biri olan enerji, tüm ülkeler için önemli bir üretim faktörüdür. Türkiye gelişmekte olan bir ülke olarak enerji talebini her geçen gün artıran bir ülkedir. Enerji krizinin yaşandığı günümüz dünyasında geleceğe yönelik güvenilir enerji tüketim tahminleri yapmak oldukça önemlidir. Bu çalışmada; ithalat, ihracat, ekonomik büyüme (Gayri Safi Yurtiçi Hasıla) ve nüfusun Türkiye'nin net enerji tüketimi üzerindeki etkilerini incelemek için yapay sinir ağları (YSA) ve uyarlamalı ağ tabanlı bulanık çıkarım sistemi (ANFIS) modelleri kullanılmıştır. YSA ve ANFIS modellerinin güvenilirliği, çeşitli istatistiksel göstergeler kullanılarak belirlenmiştir. YSA modelinde; R2, MAPE ve cov değerleri sırasıyla 0.997397669, 0.78259322 ve 5.3228538 olarak bulunmuştur. ANFIS modelinde; R2, MAPE ve cov değerleri sırasıyla 0.997845364, 0.70709233 ve 4.84339908 olarak bulunmuştur. YSA'dan elde edilen sonuçlar, aynı veri setlerinin kullanıldığı ANFIS modelinin sonuçları ile karşılaştırılmıştır. ANFIS modelinin, ANN modelinden biraz daha iyi sonuçlar verdiği görülmüştür. Eğitimli ağdan elde edilen ağırlıklar kullanılarak net enerji tüketimini belirlemek için yeni bir formül önerilmiştir. Elde edilen sonuçlar, her iki modelin de enerji tüketimini tahmin etmede başarılı bir şekilde kullanılabileceğini göstermektedir.

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Cite This Article

ŞENCAN, D., ŞAHİN, A. Ş. (2022). Estimation of Net Energy Consumption for Turkey Based on Economic Factors. El-Cezeri, Cilt: 9 - Sayı: 3, 1101–1111. https://ajindex.com/articles/662590

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