Machine Learning for Wind Forecasting is a computational methodology that employs data-driven algorithms to model and predict wind behavior by learning complex patterns from historical and real-time atmospheric data, distinguishing it from traditional physics-based forecasting approaches.
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Publications
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Citations
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Authors
930
Institutions
Publications per year
2017–2026
724
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Publications
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Support vector machines for wind speed prediction
Mohamed Mohandes, T.O. Halawani, Shafiqur Rehman et al. · Renewable Energy · 2004 · 749 citations
On comparing three artificial neural networks for wind speed forecasting
Gong Li, Jing Shi · Applied Energy · 2010 · 705 citations
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- JW
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- YZ
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- AM
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Institutions
930
North China Electric Power University
Beijing, China
43 h-index
294 publications
22.5K citations
Central South University
Changsha, China
31 h-index
115 publications
14.3K citations
Dongbei University of Finance and Economics
Dalian, China
28 h-index
64 publications
5.8K citations
Huazhong University of Science and Technology
Wuhan, China
21 h-index
90 publications
8.6K citations
Lanzhou University
Lanzhou, China
17 h-index
50 publications
8.1K citations
Guangdong University of Technology
Guangzhou, China
15 h-index
97 publications
6.9K citations
China Electric Power Research Institute
Beijing, China
15 h-index
22 publications
1.7K citations
University of South Carolina
Columbia, United States
15 h-index
19 publications
1.4K citations
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- Energy Conversion and Management
81 publications · 11.8K citations
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- Renewable Energy
79 publications · 12K citations
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- Energy
112 publications · 9K citations
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- Applied Energy
45 publications · 5.5K citations
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38 publications · 1.5K citations
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