Short-term wind power interval prediction method using VMD-RFG and Att-GRU
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DOI: 10.1016/j.energy.2022.123807
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References listed on IDEAS
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Cited by:
- Xinyue Fu & Zhongkai Feng & Xinru Yao & Wenjie Liu, 2023. "A Novel Twin Support Vector Regression Model for Wind Speed Time-Series Interval Prediction," Energies, MDPI, vol. 16(15), pages 1-23, July.
- Shi, Jinhao & Wang, Bo & Luo, Kaiyi & Wu, Yifei & Zhou, Min & Watada, Junzo, 2023. "Ultra-short-term wind power interval prediction based on multi-task learning and generative critic networks," Energy, Elsevier, vol. 272(C).
- Zhu, Qiannan & Jiang, Feng & Li, Chaoshun, 2023. "Time-varying interval prediction and decision-making for short-term wind power using convolutional gated recurrent unit and multi-objective elephant clan optimization," Energy, Elsevier, vol. 271(C).
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Keywords
Wind power; Prediction interval (PI); Neural network (NN); Fuzzy information granulation (FIG); Variational mode decomposition (VMD); Gated recurrent unit (GRU);All these keywords.
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