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Energy Sources, Part B: Economics, Planning, and Policy Volume 6, 2011 - Issue 4
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Original Articles

Energy Consumption Forecasting of Iran Using Recurrent Neural Networks

A. Avami Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
&
M. Boroushaki Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
Pages 339-347 | Received 29 Oct 2008, Accepted 16 Dec 2008, Published online: 28 Jul 2011

Citations (13)

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Xia Zhang & Weiguo Zhou. (2018) Forecast of China’s natural gas consumption using mathematical models. Energy Sources, Part B: Economics, Planning, and Policy 13:4, pages 246-250.
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Yasaman Maboudian & Kamran Rezaie. (2017) Applying data mining to investigate business continuity in petrochemical companies. Energy Sources, Part B: Economics, Planning, and Policy 12:2, pages 126-131.
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Articles from other publishers (11)

Karman Kaur. (2023) Artificial Neural Network Model to Forecast Energy Consumption in Wheat Production in India. Journal of Statistical Theory and Applications 22:1-2, pages 19-37.
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Mohammad Pasandidehpoor, João Mendes-Moreira, Soulmaz Rahman Mohammadpour & Ricardo Teixeira Sousa. 2023. Handbook of Smart Energy Systems. Handbook of Smart Energy Systems 2075 2087 .
Derya ŞENCAN & Arzu ŞENCAN ŞAHİN. (2022) Türkiye İçin Net Enerji Tüketimin Sinir Ağı ve Nöro-Bulanık Model ile Karşılaştırmalı Analizi. El-Cezeri Fen ve Mühendislik Dergisi.
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Mohammad Pasandidehpoor, João Mendes-Moreira, Soulmaz Rahman Mohammadpour & Ricardo Teixeira Sousa. 2021. Handbook of Smart Energy Systems. Handbook of Smart Energy Systems 1 13 .
Xianze Xu & Zhaorui Meng. (2020) A hybrid transfer learning model for short-term electric load forecasting. Electrical Engineering 102:3, pages 1371-1381.
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Emre YAKUT & Ezel ÖZKAN. (2020) Modeling of Energy Consumption Forecast with Economic Indicators Using Particle Swarm Optimization and Genetic Algorithm: An Application in Turkey between 1979 and 2050. Alphanumeric Journal 8:1, pages 59-78.
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Zhaorui Meng & Xianze Xu. (2019) A Hybrid Short-Term Load Forecasting Framework with an Attention-Based Encoder–Decoder Network Based on Seasonal and Trend Adjustment. Energies 12:24, pages 4612.
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Hesam Nazari & Aliyeh Kazemi. (2016) Application of PSO algorithm to choose the best scenario for energy demand forecast of residential and commercial sectors in Iran. International Journal of Energy Sector Management 10:4, pages 576-593.
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Angshuman Deka, Nima Hamta, Behzad Esmaeilian & Sara Behdad. (2016) Predictive Modeling Techniques to Forecast Energy Demand in the United States: A Focus on Economic and Demographic Factors. Journal of Energy Resources Technology 138:2.
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Sokratis Papadopoulos & Ioannis Karakatsanis. (2015) Short-term electricity load forecasting using time series and ensemble learning methods. Short-term electricity load forecasting using time series and ensemble learning methods.
Reza Pahlavan, Mahmoud Omid & Asadollah Akram. (2012) Energy input–output analysis and application of artificial neural networks for predicting greenhouse basil production. Energy 37:1, pages 171-176.
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