Using Artificial Neural Networks to Recognize the Determinants of Energy Consumption in Saudi Arabia
This study aims to investigate the variables affecting Saudi Arabia's energy consumption. To do this, the study used an innovative technique called an artificial neural network (ANN) between 2010 and 2020. The findings of this study indicate that global energy prices, followed by industrializa...
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Format: | Article |
Language: | English |
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EconJournals
2023-05-01
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Series: | International Journal of Energy Economics and Policy |
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Online Access: | http://www.econjournals.com/index.php/ijeep/article/view/13880 |
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author | Abdulrahman M. Alsobhi |
author_facet | Abdulrahman M. Alsobhi |
author_sort | Abdulrahman M. Alsobhi |
collection | DOAJ |
description |
This study aims to investigate the variables affecting Saudi Arabia's energy consumption. To do this, the study used an innovative technique called an artificial neural network (ANN) between 2010 and 2020. The findings of this study indicate that global energy prices, followed by industrialization and trade openness, are the most significant factors influencing Saudi Arabia's energy consumption. Saudi Arabia's energy consumption is not influenced by other variables, such as population growth, inflation, urbanization, economic growth, which have been addressed in other works.
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first_indexed | 2024-03-13T10:23:54Z |
format | Article |
id | doaj.art-7b5dafa3399843389a0563d9096507a1 |
institution | Directory Open Access Journal |
issn | 2146-4553 |
language | English |
last_indexed | 2024-03-13T10:23:54Z |
publishDate | 2023-05-01 |
publisher | EconJournals |
record_format | Article |
series | International Journal of Energy Economics and Policy |
spelling | doaj.art-7b5dafa3399843389a0563d9096507a12023-05-19T14:31:50ZengEconJournalsInternational Journal of Energy Economics and Policy2146-45532023-05-0113310.32479/ijeep.13880Using Artificial Neural Networks to Recognize the Determinants of Energy Consumption in Saudi ArabiaAbdulrahman M. Alsobhi0Department of Economic, College of Islamic Economy and Finance, UMM Al Qura University, Saudi Arabia. This study aims to investigate the variables affecting Saudi Arabia's energy consumption. To do this, the study used an innovative technique called an artificial neural network (ANN) between 2010 and 2020. The findings of this study indicate that global energy prices, followed by industrialization and trade openness, are the most significant factors influencing Saudi Arabia's energy consumption. Saudi Arabia's energy consumption is not influenced by other variables, such as population growth, inflation, urbanization, economic growth, which have been addressed in other works. http://www.econjournals.com/index.php/ijeep/article/view/13880Saudi Arabia, Energy consumption, Artificial neural network |
spellingShingle | Abdulrahman M. Alsobhi Using Artificial Neural Networks to Recognize the Determinants of Energy Consumption in Saudi Arabia International Journal of Energy Economics and Policy Saudi Arabia, Energy consumption, Artificial neural network |
title | Using Artificial Neural Networks to Recognize the Determinants of Energy Consumption in Saudi Arabia |
title_full | Using Artificial Neural Networks to Recognize the Determinants of Energy Consumption in Saudi Arabia |
title_fullStr | Using Artificial Neural Networks to Recognize the Determinants of Energy Consumption in Saudi Arabia |
title_full_unstemmed | Using Artificial Neural Networks to Recognize the Determinants of Energy Consumption in Saudi Arabia |
title_short | Using Artificial Neural Networks to Recognize the Determinants of Energy Consumption in Saudi Arabia |
title_sort | using artificial neural networks to recognize the determinants of energy consumption in saudi arabia |
topic | Saudi Arabia, Energy consumption, Artificial neural network |
url | http://www.econjournals.com/index.php/ijeep/article/view/13880 |
work_keys_str_mv | AT abdulrahmanmalsobhi usingartificialneuralnetworkstorecognizethedeterminantsofenergyconsumptioninsaudiarabia |