Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm
© 2019 Elsevier Ltd It is hard to predict wind power with high-precision due to its non-stationary and stochastic nature. The wind power has developed rapidly around the world as a promising renewable energy industry. The uncertainty of wind power brings difficult challenges to the operation of the...
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Main Authors: | Li, Ling Ling, Zhao, Xue, Tseng, Ming Lang, Tan, Raymond Girard R. |
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Format: | text |
Published: |
Animo Repository
2020
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Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/895 https://animorepository.dlsu.edu.ph/context/faculty_research/article/1894/type/native/viewcontent |
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Institution: | De La Salle University |
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