File:Forecasting of energy consumption by G20 countries using an adjacent accumulation grey model.pdf
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[edit]DescriptionForecasting of energy consumption by G20 countries using an adjacent accumulation grey model.pdf |
English: This paper studies an adjacent accumulation discrete grey model to improve the prediction of the grey model and enhance the utilization of new data. The impact of COVID-19 on the global economy is also discussed. Two cases are discussed to prove the stability of the adjacent accumulation discrete grey model, which helped the studied model attain higher forecasting accuracy. Using the adjacent accumulation discrete grey model, non-renewable energy consumption in G20 countries from 2022 to 2026 is predicted based on their consumption data from 2011 to 2021. It is proven that the adjacent accumulation exhibits sufficient accuracy and precision. Forecasting results obtained in this paper show that energy consumption of all the non-renewable sources other than coal has an increasing trend during the forecasting period, with the USA, Russia, and China being the biggest consumers. Natural gas is the most consumed non-renewable energy source between 2022 and 2026, whereas hydroelectricity is the least consumed. The USA is the biggest consumer of Nuclear energy among the G20 countries, whereas Argentina consumed only 0.1 Exajoules of nuclear energy, placing it at the end of nuclear energy consumers. |
Date | |
Source | https://www.nature.com/articles/s41598-022-17505-4 |
Author | Ijlal Raheem, Nabisab Mujawar Mubarak, Rama Rao Karri, T. Manoj, Sobhy M. Ibrahim, Shaukat Ali Mazari & Sabzoi Nizamuddin |
doi:10.1038/s41598-022-17505-4
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current | 07:00, 14 August 2022 | 1,239 × 1,629, 23 pages (3.94 MB) | Koavf (talk | contribs) | Uploaded a work by Ijlal Raheem, Nabisab Mujawar Mubarak, Rama Rao Karri, T. Manoj, Sobhy M. Ibrahim, Shaukat Ali Mazari & Sabzoi Nizamuddin from https://www.nature.com/articles/s41598-022-17505-4 with UploadWizard |
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Publisher | Nature Publishing Group UK |
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Date and time of digitizing | 18:56, 4 August 2022 |
Software used | Springer |
File change date and time | 16:10, 4 August 2022 |
Date metadata was last modified | 16:10, 4 August 2022 |
Identifier | https://doi.org/10.1038/s41598-022-17505-4 |
Conversion program | Adobe PDF Library 15.0; modified using iText® 5.3.5 ©2000-2012 1T3XT BVBA (SPRINGER SBM; licensed version) |
Encrypted | no |
Page size | 595.276 x 782.362 pts |
Version of PDF format | 1.4 |