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Near real-time wind speed forecast model with bidirectional LSTM networks

Citations

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Cited by:

  1. Zhang, Dongdong & Chen, Baian & Zhu, Hongyu & Goh, Hui Hwang & Dong, Yunxuan & Wu, Thomas, 2023. "Short-term wind power prediction based on two-layer decomposition and BiTCN-BiLSTM-attention model," Energy, Elsevier, vol. 285(C).
  2. Dong, Juan & Xing, Liwen & Cui, Ningbo & Zhao, Lu & Guo, Li & Wang, Zhihui & Du, Taisheng & Tan, Mingdong & Gong, Daozhi, 2024. "Estimating reference crop evapotranspiration using improved convolutional bidirectional long short-term memory network by multi-head attention mechanism in the four climatic zones of China," Agricultural Water Management, Elsevier, vol. 292(C).
  3. Chen, Zhengganzhe & Zhang, Bin & Du, Chenglong & Meng, Wei & Meng, Anbo, 2024. "A novel dynamic spatio-temporal graph convolutional network for wind speed interval prediction," Energy, Elsevier, vol. 294(C).
  4. Wu, Binrong & Wang, Lin, 2024. "Two-stage decomposition and temporal fusion transformers for interpretable wind speed forecasting," Energy, Elsevier, vol. 288(C).
  5. Sun, Yang & Tian, Zhirui, 2025. "Solving few-shot problem in wind speed prediction: A novel transfer strategy based on decomposition and learning ensemble," Applied Energy, Elsevier, vol. 377(PD).
  6. Zhang, Yagang & Wang, Hui & Wang, Jingchao & Cheng, Xiaodan & Wang, Tong & Zhao, Zheng, 2024. "Ensemble optimization approach based on hybrid mode decomposition and intelligent technology for wind power prediction system," Energy, Elsevier, vol. 292(C).
  7. Zhang, Chu & Li, Zhengbo & Ge, Yida & Liu, Qianlong & Suo, Leiming & Song, Shihao & Peng, Tian, 2024. "Enhancing short-term wind speed prediction based on an outlier-robust ensemble deep random vector functional link network with AOA-optimized VMD," Energy, Elsevier, vol. 296(C).
  8. Lakhdar Nadjib Boucetta & Youssouf Amrane & Aissa Chouder & Saliha Arezki & Sofiane Kichou, 2024. "Enhanced Forecasting Accuracy of a Grid-Connected Photovoltaic Power Plant: A Novel Approach Using Hybrid Variational Mode Decomposition and a CNN-LSTM Model," Energies, MDPI, vol. 17(7), pages 1-21, April.
  9. Manoharan Madhiarasan & S. N. Deepa & N. Yogambal Jayalakshmi, 2025. "Hyperparameter optimization of a deep radial basis neural learning approach for wind speed forecasting," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 16(9), pages 3053-3074, September.
  10. Zhu, Yingqin & Liu, Yue & Wang, Nan & Zhang, ZhaoZhao & Li, YuanQiang, 2025. "Real-time Error Compensation Transfer Learning with Echo State Networks for Enhanced Wind Power Prediction," Applied Energy, Elsevier, vol. 379(C).
  11. Wu, Binrong & Yu, Sihao & Peng, Lu & Wang, Lin, 2024. "Interpretable wind speed forecasting with meteorological feature exploring and two-stage decomposition," Energy, Elsevier, vol. 294(C).
  12. Jiang, Wenjun & Liu, Bo & Liang, Yang & Gao, Huanxiang & Lin, Pengfei & Zhang, Dongqin & Hu, Gang, 2024. "Applicability analysis of transformer to wind speed forecasting by a novel deep learning framework with multiple atmospheric variables," Applied Energy, Elsevier, vol. 353(PB).
  13. Wang, Shuangxin & Shi, Jiarong & Yang, Wei & Yin, Qingyan, 2024. "High and low frequency wind power prediction based on Transformer and BiGRU-Attention," Energy, Elsevier, vol. 288(C).
  14. Liang, Yang & Zhang, Dongqin & Zhang, Jize & Hu, Gang, 2024. "A state-of-the-art analysis on decomposition method for short-term wind speed forecasting using LSTM and a novel hybrid deep learning model," Energy, Elsevier, vol. 313(C).
  15. Wang, Jujie & Liu, Yafen & Li, Yaning, 2024. "A parallel differential learning ensemble framework based on enhanced feature extraction and anti-information leakage mechanism for ultra-short-term wind speed forecast," Applied Energy, Elsevier, vol. 361(C).
  16. Joseph, Lionel P. & Deo, Ravinesh C. & Casillas-Pérez, David & Prasad, Ramendra & Raj, Nawin & Salcedo-Sanz, Sancho, 2024. "Short-term wind speed forecasting using an optimized three-phase convolutional neural network fused with bidirectional long short-term memory network model," Applied Energy, Elsevier, vol. 359(C).
  17. Wang, Yaqi & Zhao, Xiaomeng & Li, Zheng & Zhu, Wenbo & Gui, Renzhou, 2024. "A novel hybrid model for multi-step-ahead forecasting of wind speed based on univariate data feature enhancement," Energy, Elsevier, vol. 312(C).
  18. Li, Xuehan & Wang, Wei & Fang, Fang & Liu, Jizhen & Chen, Zhe, 2025. "Improving active power regulation for wind turbine by phase leading cascaded error-based active disturbance rejection control and multi-objective optimization," Renewable Energy, Elsevier, vol. 243(C).
  19. Feng, Ganghui & Wang, Shu & Zhao, Xuan & Hu, Shun & Lv, Yang, 2025. "Online adaptive shift control method for heavy-duty electric commercial vehicles considering road slope and shift frequency," Energy, Elsevier, vol. 335(C).
  20. Zhengxuan Xiao & Fei Tang & Mengyuan Wang, 2023. "Wind Power Short-Term Forecasting Method Based on LSTM and Multiple Error Correction," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
  21. Shengxiang Lv & Lin Wang & Sirui Wang, 2023. "A Hybrid Neural Network Model for Short-Term Wind Speed Forecasting," Energies, MDPI, vol. 16(4), pages 1-18, February.
  22. Xiang, Ling & Fu, Xiaomengting & Yao, Qingtao & Zhu, Guopeng & Hu, Aijun, 2024. "A novel model for ultra-short term wind power prediction based on Vision Transformer," Energy, Elsevier, vol. 294(C).
  23. Yanhui Liu & Jiulong Wang & Lingyun Song & Yicheng Liu & Liqun Shen, 2025. "Enhanced Short-Term PV Power Forecasting via a Hybrid Modified CEEMDAN-Jellyfish Search Optimized BiLSTM Model," Energies, MDPI, vol. 18(13), pages 1-22, July.
  24. Wang, Yufeng & Yang, Zihan & Ma, Jianhua & Jin, Qun, 2024. "A wind speed forecasting framework for multiple turbines based on adaptive gate mechanism enhanced multi-graph attention networks," Applied Energy, Elsevier, vol. 372(C).
  25. Kinzah Noor & Agbotiname Lucky Imoize & Chun-Ta Li & Chi-Yao Weng, 2025. "A Review of Machine Learning and Transfer Learning Strategies for Intrusion Detection Systems in 5G and Beyond," Mathematics, MDPI, vol. 13(7), pages 1-63, March.
  26. Wang, Jujie & Jiang, Weiyi & Shu, Shuqin & He, Xuecheng, 2025. "A multi-factor clustering integration paradigm for wind speed point-interval prediction based on feature selection and optimized inverted transformer," Energy, Elsevier, vol. 320(C).
  27. Li, Yanhui & Sun, Kaixuan & Yao, Qi & Wang, Lin, 2024. "A dual-optimization wind speed forecasting model based on deep learning and improved dung beetle optimization algorithm," Energy, Elsevier, vol. 286(C).
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