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Scopus YÖKSİS DOI Eşleşti SJR Q2

Long term electricity demand forecasting in Turkey using artificial neural networks

Energy Sources Part B Economics Planning and Policy · Temmuz 2010

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YÖKSİS Kayıtları
Long Term Electricity Demand Forecasting in Turkey Using Artificial Neural Networks
Energy Sources, Part B: Economics, Planning, and Policy · 2010 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
Long Term Electricity Demand Forecasting in Turkey Using Artificial Neural Networks
Energy Sources, Part B: Economics, Planning, and Policy · 2010 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
YÖKSİS ISSN Eşleşmesi

Bu dergide (ISSN eşleşmesi) kurumun 4 kaydı bulundu.

YÖKSİS Kayıtları — ISSN Eşleşmesi
Long Term Electricity Demand Forecasting in Turkey Using Artificial Neural Networks
2010 ISSN: 1556-7249 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
Turkey s Electricity Consumption Forecasting Using Genetic Programming
2011 ISSN: 1556-7249 SCI-Expanded
Dr. Öğr. Üyesi UĞUR TAŞKIRAN →
Long Term Electricity Demand Forecasting in Turkey Using Artificial Neural Networks
2010 ISSN: 1556-7249 SCI-Expanded
Prof. Dr. ADEM ALPASLAN ALTUN →
Turkey s Electricity Consumption Forecasting Using Genetic Programming
2011 ISSN: 1556-7249 SCI-Expanded
Dr. Öğr. Üyesi UĞUR TAŞKIRAN →

Makale Bilgileri

Dergi Energy Sources Part B Economics Planning and Policy
ISSN15567249
Yayın TarihiTemmuz 2010
Cilt / Sayfa5 · 279-289
DOI10.1080/15567240802533542
Scopus ID2-s2.0-77954924900
Özet This article presents an approach for Turkey's long-term electricity demand forecasting. Two Artificial Neural Network structures, three-layered back-propagation and a recurrent neural network are designed and tested for this purpose. Predictions are done for the years 2008 to 2014. Since long-term forecasting is mainly influenced by economic factors, this study focuses on economic data. The proposed approach produces lower percent errors, especially in the recurrent neural network. The forecast results by artificial neural networks are also compared with official forecasts. Copyright © 2010 Taylor & Francis Group, LLC.

Yazarlar (2)

1
Mehmet Çunkaş
2
A. A. Altun

Anahtar Kelimeler

artificial neural networks economic factors load forecasting Turkey

Kurumlar

Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Energy Sources, Part B: Economics, Planning and Policy
Q2
SJR Skoru0,620
H-Index57
YayıncıTaylor and Francis Ltd.
ÜlkeUnited Kingdom
Chemical Engineering (miscellaneous) (Q2)
Energy Engineering and Power Technology (Q2)
Environmental Science (miscellaneous) (Q2)
Fuel Technology (Q2)
Nuclear Energy and Engineering (Q2)
Renewable Energy, Sustainability and the Environment (Q2)
Dergi sayfasına git

Metrikler

55
Atıf
2
Yazar
4
Anahtar Kelime

Sistemimizdeki Yazarlar

MÇ
MEHMET ÇUNKAŞ
Prof. Dr.

Hızlı Erişim

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