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A combined short-term wind speed forecasting model based on CNN–RNN and linear regression optimization considering error

Citations

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  1. Jie Du & Shuaizhi Chen & Linlin Pan & Yubao Liu, 2025. "A Wind Speed Prediction Method Based on Signal Decomposition Technology Deep Learning Model," Energies, MDPI, vol. 18(5), pages 1-26, February.
  2. Zheng, Xidong & Bai, Feifei & Zeng, Ziyang & Jin, Tao, 2024. "A new methodology to improve wind power prediction accuracy considering power quality disturbance dimension reduction and elimination," Energy, Elsevier, vol. 287(C).
  3. 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).
  4. Wang, Jujie & Shu, Shuqin & Xu, Shulian, 2025. "A point-interval wind speed prediction model based on entropy clustering and hybrid optimization weighted strategy," Renewable Energy, Elsevier, vol. 244(C).
  5. 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).
  6. Yang, Zhaoming & Liu, Zhe & Zhou, Jing & Song, Chaofan & Xiang, Qi & He, Qian & Hu, Jingjing & Faber, Michael H. & Zio, Enrico & Li, Zhenlin & Su, Huai & Zhang, Jinjun, 2023. "A graph neural network (GNN) method for assigning gas calorific values to natural gas pipeline networks," Energy, Elsevier, vol. 278(C).
  7. 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.
  8. 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).
  9. Wen, Yan & Pan, Su & Li, Xinxin & Li, Zibo & Wen, Wuzhenghong, 2024. "Improving multi-site photovoltaic forecasting with relevance amplification: DeepFEDformer-based approach," Energy, Elsevier, vol. 299(C).
  10. 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).
  11. Maria Ashraf & Bushra Raza & Maryam Arshad & Bilal Muhammad Khan & Syed Sajjad Haider Zaidi, 2024. "Performance enhancement of short-term wind speed forecasting model using Realtime data," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-19, May.
  12. Li, Qingyang & Wang, Guosong & Wu, Xinrong & Gao, Zhigang & Dan, Bo, 2024. "Arctic short-term wind speed forecasting based on CNN-LSTM model with CEEMDAN," Energy, Elsevier, vol. 299(C).
  13. Muyuan Du & Zhimeng Zhang & Chunning Ji, 2025. "Prediction for Coastal Wind Speed Based on Improved Variational Mode Decomposition and Recurrent Neural Network," Energies, MDPI, vol. 18(3), pages 1-28, January.
  14. Sun, Xiaoying & Liu, Haizhong, 2024. "Multivariate short-term wind speed prediction based on PSO-VMD-SE-ICEEMDAN two-stage decomposition and Att-S2S," Energy, Elsevier, vol. 305(C).
  15. Zhang, Zeguo & Yin, Jianchuan, 2025. "Incremental principal component analysis based depthwise separable Unet model for complex wind system forecasting," Energy, Elsevier, vol. 334(C).
  16. Suo, Leiming & Peng, Tian & Song, Shihao & Zhang, Chu & Wang, Yuhan & Fu, Yongyan & Nazir, Muhammad Shahzad, 2023. "Wind speed prediction by a swarm intelligence based deep learning model via signal decomposition and parameter optimization using improved chimp optimization algorithm," Energy, Elsevier, vol. 276(C).
  17. Zang, Haixiang & Li, Wenan & Cheng, Lilin & Liu, Jingxuan & Wei, Zhinong & Sun, Guoqiang, 2025. "Short-term multi-site solar irradiance prediction with dynamic-graph-convolution-based spatial-temporal correlation capturing," Renewable Energy, Elsevier, vol. 246(C).
  18. Li, Yang & Feng, Haibo, 2025. "Integrating urban building energy modeling (UBEM) and urban-building environmental impact assessment (UB-EIA) for sustainable urban development: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 213(C).
  19. Lv, Sheng-Xiang & Wang, Lin, 2023. "Multivariate wind speed forecasting based on multi-objective feature selection approach and hybrid deep learning model," Energy, Elsevier, vol. 263(PE).
  20. Mirza, Adeel Feroz & Shu, Zhaokun & Usman, Muhammad & Mansoor, Majad & Ling, Qiang, 2024. "Quantile-transformed multi-attention residual framework (QT-MARF) for medium-term PV and wind power prediction," Renewable Energy, Elsevier, vol. 220(C).
  21. Wang Xinxin & Shen Xiaopan & Ai Xueyi & Li Shijia, 2023. "Short-term wind speed forecasting based on a hybrid model of ICEEMDAN, MFE, LSTM and informer," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-27, September.
  22. Qu, Zhijian & Hou, Xinxing & Li, Jian & Hu, Wenbo, 2024. "Short-term wind farm cluster power prediction based on dual feature extraction and quadratic decomposition aggregation," Energy, Elsevier, vol. 290(C).
  23. Song, Weiye & Yan, Jie & Han, Shuang & Liu, Shihua & Wang, Han & Dai, Qiangsheng & Huo, Xuesong & Liu, Yongqian, 2024. "A multi-task spatio-temporal fusion network for offshore wind power ramp events forecasting," Renewable Energy, Elsevier, vol. 237(PB).
  24. Ma, Jiawei & Du, Jie & Chen, Qixian & Jiang, Xinyu & Pan, Linlin, 2025. "Multi-feature extraction spatio-temporal interaction graph network for wind speed forecasting in windfarm," Energy, Elsevier, vol. 333(C).
  25. 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).
  26. Xiao, Yiping & Wei, Honghao & Shi, Ying & Zhang, Haiyang & Shen, Zongtao & Jiao, Hongjian, 2025. "A short-term wind power prediction based on MCOOT optimized deep learning networks and attention-weighted environmental factors for error correction," Energy, Elsevier, vol. 324(C).
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