CANLI
Yükleniyor Veriler getiriliyor…
SCI-Expanded Özgün Makale Scopus
Long Term Electricity Demand Forecasting in Turkey Using Artificial Neural Networks
Energy Sources, Part B: Economics, Planning, and Policy 2010 Cilt 5 Sayı 3
Scopus Eşleşmesi Bulundu
46
Atıf
5
Cilt
279-289
Sayfa
Scopus Yazarları: A. A. Altun, Mehmet Çunkaş
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.
Anahtar Kelimeler (Scopus)
artificial neural networks load forecasting Turkey economic factors
Scimago Dergi Bilgisi Otomatik ISSN Eşleştirmesi 2010 yılı verileri
Energy Sources, Part B: Economics, Planning and Policy
Q1
SJR Quartile
0,584
SJR Skoru
57
H-Index
Kategoriler: Chemical Engineering (miscellaneous) (Q1) · Energy Engineering and Power Technology (Q1) · Fuel Technology (Q1) · Environmental Science (miscellaneous) (Q2) · Nuclear Energy and Engineering (Q2) · Renewable Energy, Sustainability and the Environment (Q2)
Alanlar: Chemical Engineering · Energy · Environmental Science
Ülke: United Kingdom · Taylor and Francis Ltd.
Bu bilgiler makale yılına göre Scimago veritabanından ISSN eşleştirmesiyle otomatik getirilmektedir. Dergi sıralama verileri Scimago'nun ilgili yılı baz alınmaktadır.

Anahtar Kelimeler

artificial neural networks load forecasting Turkey economic factors

Makale Bilgileri

Dergi Energy Sources, Part B: Economics, Planning, and Policy
ISSN 1556-7249
Yıl 2010 / 6. ay
Cilt / Sayı 5 / 3
Sayfalar 279 – 289
Makale Türü Özgün Makale
Hakemlik Hakemli
Endeks SCI-Expanded
Yayın Dili İngilizce
Kapsam Uluslararası
Toplam Yazar 2 kişi
Erişim Türü Elektronik
Erişim Linki Makaleye Git
Alan Mühendislik Temel Alanı- Elektrik-Elektronik Mühendisliği

YÖKSİS Yazar Kaydı

Yazar Adı ÇUNKAŞ MEHMET,ALTUN ADEM ALPASLAN
YÖKSİS ID 373598