IDEAS home Printed from https://ideas.repec.org/r/eee/energy/v265y2023ics0360544222032698.html
   My bibliography  Save this item

Hybrid wind speed forecasting using ICEEMDAN and transformer model with novel loss function

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Yang, Mao & Jiang, Yue & Zhang, Wei & Li, Yi & Su, Xin, 2024. "Short-term interval prediction strategy of photovoltaic power based on meteorological reconstruction with spatiotemporal correlation and multi-factor interval constraints," Renewable Energy, Elsevier, vol. 237(PC).
  2. Wu, Binrong & Wang, Lin, 2024. "Two-stage decomposition and temporal fusion transformers for interpretable wind speed forecasting," Energy, Elsevier, vol. 288(C).
  3. Zhe Dong & Yiyang Zhao & Anqi Wang & Meng Zhou, 2025. "Wind-Mambaformer: Ultra-Short-Term Wind Turbine Power Forecasting Based on Advanced Transformer and Mamba Models," Energies, MDPI, vol. 18(5), pages 1-22, February.
  4. Wu, Zhiyuan & Fang, Guohua & Ye, Jian & Zhu, David Z. & Huang, Xianfeng, 2025. "A reinforcement learning-based ensemble forecasting framework for renewable energy forecasting," Renewable Energy, Elsevier, vol. 244(C).
  5. Yang, Mao & Guo, Yunfeng & Fan, Fulin & Huang, Tao, 2024. "Two-stage correction prediction of wind power based on numerical weather prediction wind speed superposition correction and improved clustering," Energy, Elsevier, vol. 302(C).
  6. Yang, Dongchuan & Li, Mingzhu & Guo, Ju-e & Du, Pei, 2024. "An attention-based multi-input LSTM with sliding window-based two-stage decomposition for wind speed forecasting," Applied Energy, Elsevier, vol. 375(C).
  7. 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).
  8. 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).
  9. Yang, Mao & Guo, Yunfeng & Huang, Yutong, 2023. "Wind power ultra-short-term prediction method based on NWP wind speed correction and double clustering division of transitional weather process," Energy, Elsevier, vol. 282(C).
  10. Lin, Shengmao & Wang, Shu & Xu, Xuefang & Li, Ruixiong & Shi, Peiming, 2024. "GAOformer: An adaptive spatiotemporal feature fusion transformer utilizing GAT and optimizable graph matrixes for offshore wind speed prediction," Energy, Elsevier, vol. 292(C).
  11. Jialin Liu & Chen Gong & Suhua Chen & Nanrun Zhou, 2023. "Multi-Step-Ahead Wind Speed Forecast Method Based on Outlier Correction, Optimized Decomposition, and DLinear Model," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
  12. Zhang, Yagang & Kong, Xue & Wang, Jingchao & Wang, Hui & Cheng, Xiaodan, 2024. "Wind power forecasting system with data enhancement and algorithm improvement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 196(C).
  13. Xiong, Zhanhang & Yao, Jianjiang & Huang, Yongmin & Yu, Zhaoxu & Liu, Yalei, 2024. "A wind speed forecasting method based on EMD-MGM with switching QR loss function and novel subsequence superposition," Applied Energy, Elsevier, vol. 353(PB).
  14. Hou, Guolian & Wang, Junjie & Fan, Yuzhen, 2024. "Multistep short-term wind power forecasting model based on secondary decomposition, the kernel principal component analysis, an enhanced arithmetic optimization algorithm, and error correction," Energy, Elsevier, vol. 286(C).
  15. Shengcai Zhang & Changsheng Zhu & Xiuting Guo, 2024. "Wind-Speed Multi-Step Forecasting Based on Variational Mode Decomposition, Temporal Convolutional Network, and Transformer Model," Energies, MDPI, vol. 17(9), pages 1-22, April.
  16. Lin, Qingcheng & Cai, Huiling & Liu, Hanwei & Li, Xuefeng & Xiao, Hui, 2024. "A novel ultra-short-term wind power prediction model jointly driven by multiple algorithm optimization and adaptive selection," Energy, Elsevier, vol. 288(C).
  17. Zhang, Guowei & Zhang, Yi & Wang, Hui & Liu, Da & Cheng, Runkun & Yang, Di, 2024. "Short-term wind speed forecasting based on adaptive secondary decomposition and robust temporal convolutional network," Energy, Elsevier, vol. 288(C).
  18. Chen, Yaoran & Cai, Candong & Cao, Leilei & Zhang, Dan & Kuang, Limin & Peng, Yan & Pu, Huayan & Wu, Chuhan & Zhou, Dai & Cao, Yong, 2024. "WindFix: Harnessing the power of self-supervised learning for versatile imputation of offshore wind speed time series," Energy, Elsevier, vol. 287(C).
  19. Leng, Zhiyuan & Chen, Lu & Yi, Bin & Liu, Fanqian & Xie, Tao & Mei, Ziyi, 2025. "Short-term wind speed forecasting based on a novel KANInformer model and improved dual decomposition," Energy, Elsevier, vol. 322(C).
  20. 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).
  21. 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).
  22. He, Jinhua & Hu, Zechun & Wang, Songpo & Mujeeb, Asad & Yang, Pengwei, 2024. "Windformer: A novel 4D high-resolution system for multi-step wind speed vector forecasting based on temporal shifted window multi-head self-attention," Energy, Elsevier, vol. 310(C).
  23. Wang, Chao & Lin, Hong & Yang, Ming & Fu, Xiaoling & Yuan, Yue & Wang, Zewei, 2024. "A novel chaotic time series wind power point and interval prediction method based on data denoising strategy and improved coati optimization algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
  24. 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.
  25. Parri, Srihari & Teeparthi, Kiran & Kosana, Vishalteja, 2024. "A hybrid methodology using VMD and disentangled features for wind speed forecasting," Energy, Elsevier, vol. 288(C).
  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. Chen, Bingyang & Zeng, Xingjie & Zhang, Weishan & Fan, Lulu & Cao, Shaohua & Zhou, Jiehan, 2023. "Knowledge sharing-based multi-block federated learning for few-shot oil layer identification," Energy, Elsevier, vol. 283(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.