Open Access
Issue
E3S Web of Conf.
Volume 540, 2024
1st International Conference on Power and Energy Systems (ICPES 2023)
Article Number 03009
Number of page(s) 9
Section Wind Turbine and Energy Systems
DOI https://doi.org/10.1051/e3sconf/202454003009
Published online 21 June 2024
  1. Margarat, G. S., Kumar, S., & Rajan, S. (2023). Forecasting Wind Energy Production Using Machine Learning Techniques. In E3S Web of Conferences (Vol. 387, p. 01007). EDP Sciences. [CrossRef] [EDP Sciences] [Google Scholar]
  2. Benti, N. E., Chaka, M. D., & Semie, A. G. (2023). Forecasting Renewable Energy Generation with Machine learning and Deep Learning: Current Advances and Future Prospects. Sustainability, 15(9), 7087 [CrossRef] [Google Scholar]
  3. M. E. Şahin and T. K. Şahin, Renewable and Sustainable Energy Reviews, vol. 76, pp. 31–42, (2017). [Google Scholar]
  4. M. El-hajj, J. El-hajj, and E. Hajj, Energy Conversion and Management, vol. 150, pp. 205–215, (2017). [Google Scholar]
  5. X. Gao, B. Xue, and H. Chen, Energy Conversion and Management, vol. 108, pp. 372–382, (2016). [Google Scholar]
  6. Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255–260. [CrossRef] [Google Scholar]
  7. Carbonell, J. G., Michalski, R. S., & Mitchell, T. M. (1983). An overview of machine learning. Machine learning, 3–23. [Google Scholar]
  8. Wang, H., Ma, C., & Zhou, L. (2009, December). A brief review of machine learning and its application. In 2009 international conference on information engineering and computer science (pp. 1–4). IEEE. [Google Scholar]
  9. Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A review. Sensors, 18(8), 2674 [CrossRef] [Google Scholar]
  10. Alanne, K., & Sierla, S. (2022). An overview of machine learning applications for smart buildings. Sustainable Cities and Society, 76, 103445 [CrossRef] [Google Scholar]

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