A survey on advanced machine learning and deep learning techniques assisting in renewable energy generation
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11356-023-29064-w.pdf
Reference94 articles.
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2. Abd El-Aziz RM (2022) Renewable power source energy consumption by hybrid machine learning model. Alex Eng J 61(12):9447–9455. https://doi.org/10.1016/j.aej.2022.03.019
3. Abedinia O, Amjady N, Ghadimi N (2018) Solar energy forecasting based on hybrid neural network and improved metaheuristic algorithm. Comput Intell 34(1):241–260. https://doi.org/10.1111/coin.12145
4. Al-Othman A, Tawalbeh M, Martis R, Dhou S, Orhan M, Qasim M, Olabi AG (2022) Artificial intelligence and numerical models in hybrid renewable energy systems with fuel cells: advances and prospects. Energy Convers Manag 253:115154. https://doi.org/10.1016/j.enconman.2021.115154
5. Antonopoulos I, Robu V, Couraud B, Kirli D, Norbu S, Kiprakis A, Flynn D, Elizondo-Gonzalez S, Wattam S (2020) Artificial intelligence and machine learning approaches to energy demand-side response: a systematic review. Renew Sustain Energ Rev 130:109899. https://doi.org/10.1016/j.rser.2020.109899
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