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Darvishi Salookolaei, D., Babaei, P., Heydari gorji, S.. (1398). Prediction of Renewable Energy Production Using Grey Systems Theory. هنرهای کاربردی, 10(Special Issue ( Nonlinear Analysis in Engineering and Sciences)), 39-51. doi: 10.22075/ijnaa.2019.4395
D. Darvishi Salookolaei; P. Babaei; S. Heydari gorji. "Prediction of Renewable Energy Production Using Grey Systems Theory". هنرهای کاربردی, 10, Special Issue ( Nonlinear Analysis in Engineering and Sciences), 1398, 39-51. doi: 10.22075/ijnaa.2019.4395
Darvishi Salookolaei, D., Babaei, P., Heydari gorji, S.. (1398). 'Prediction of Renewable Energy Production Using Grey Systems Theory', هنرهای کاربردی, 10(Special Issue ( Nonlinear Analysis in Engineering and Sciences)), pp. 39-51. doi: 10.22075/ijnaa.2019.4395
Darvishi Salookolaei, D., Babaei, P., Heydari gorji, S.. Prediction of Renewable Energy Production Using Grey Systems Theory. هنرهای کاربردی, 1398; 10(Special Issue ( Nonlinear Analysis in Engineering and Sciences)): 39-51. doi: 10.22075/ijnaa.2019.4395

Prediction of Renewable Energy Production Using Grey Systems Theory

International Journal of Nonlinear Analysis and Applications
مقاله 4، دوره 10، Special Issue ( Nonlinear Analysis in Engineering and Sciences)، اسفند 2019، صفحه 39-51    اصل مقاله (195.03 K)
نوع مقاله: Special issue editorial
شناسه دیجیتال (DOI): 10.22075/ijnaa.2019.4395
نویسندگان
D. Darvishi Salookolaei* 1؛ P. Babaei1؛ S. Heydari gorji2
1Department of Mathematics, Payame Noor University, Tehran, Iran
2Department of Management, Payame Noor University, Tehran, Iran
تاریخ دریافت: 15 تیر 1398،  تاریخ بازنگری: 12 شهریور 1398،  تاریخ پذیرش: 20 شهریور 1398 
چکیده
Due to the reduction of renewable energy resources such as fossil fuels, the energy crisis is one of the most critical issues in today’s world. The application of these resources brings about many environmental pollutions that lead to global warming. Therefore, various countries have attempted to reduce potential damage and use renewable energies by the introduction and promotion of renewable energies as an essential strategy to reduce CO2 emissions and to find alternatives to fossil energy in the transportation and electricity generation sectors. This study attempts to predict the production process of renewable energies in Iran by 2025 and study the characteristics of this energy and its usage in the world and Iran. Since there are very few data in this field, four grey prediction models are used including GM(1,1), DGM(2,1), Grey Verhulst and FGM(1,1) models. According to the three indices of the error values of MSE, RMSE, and MAPE, all the predictions are done by the methods above are among the best prediction methods. By examining the results achieved, FGM(1,1)method was the best model concerning its less error than other models and has estimated 16740.45 MW for renewable energy production in 2025. 
کلیدواژه‌ها
Prediction؛ Grey system؛ Absolute prediction error؛ Renewable Energy؛ GM(1؛ 1)
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