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A convolutional Transformer-based truncated Gaussian density network with data denoising for wind speed forecasting

Citations

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Cited by:

  1. Wang, Yun & Duan, Xiaocong & Zhang, Fan & Wu, Guang & Zou, Runmin & Wan, Jie & Hu, Qinghua, 2025. "MFFDM-WLS: A multi-granularity feature-based coherent forecasting method for temporal hierarchical wind speed time series," Applied Energy, Elsevier, vol. 400(C).
  2. Talaat, Fatma M. & Kabeel, A.E. & Shaban, Warda M., 2024. "The role of utilizing artificial intelligence and renewable energy in reaching sustainable development goals," Renewable Energy, Elsevier, vol. 235(C).
  3. Cheng, Fang & Liu, Hui, 2024. "Multi-step electric vehicles charging loads forecasting: An autoformer variant with feature extraction, frequency enhancement, and error correction blocks," Applied Energy, Elsevier, vol. 376(PB).
  4. Xilong Lin & Yisen Niu & Zixuan Yan & Lianglin Zou & Ping Tang & Jifeng Song, 2024. "Hybrid Photovoltaic Output Forecasting Model with Temporal Convolutional Network Using Maximal Information Coefficient and White Shark Optimizer," Sustainability, MDPI, vol. 16(14), pages 1-20, July.
  5. Yin, Linfei & Zhou, Hang, 2024. "Modal decomposition integrated model for ultra-supercritical coal-fired power plant reheater tube temperature multi-step prediction," Energy, Elsevier, vol. 292(C).
  6. Wang, Yun & Song, Mengmeng & Yang, Dazhi, 2024. "Local-global feature-based spatio-temporal wind speed forecasting with a sparse and dynamic graph," Energy, Elsevier, vol. 289(C).
  7. Wang, Ying & Li, Hongmin & Jahanger, Atif & Li, Qiwei & Wang, Biao & Balsalobre-Lorente, Daniel, 2024. "A novel ensemble electricity load forecasting system based on a decomposition-selection-optimization strategy," Energy, Elsevier, vol. 312(C).
  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. Antonesi, Gabriel & Cioara, Tudor & Anghel, Ionut & Michalakopoulos, Vasilis & Sarmas, Elissaios & Toderean, Liana, 2025. "A systematic review of transformers and large language models in the energy sector: towards agentic digital twins," Applied Energy, Elsevier, vol. 401(PA).
  10. Wang, Sen & Sun, Yonghui & Zhang, Wenjie & Chung, C.Y. & Srinivasan, Dipti, 2024. "Very short-term wind power forecasting considering static data: An improved transformer model," Energy, Elsevier, vol. 312(C).
  11. 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).
  12. Hu, Jiaxiang & Hu, Weihao & Cao, Di & Huang, Yuehui & Chen, Jianjun & Li, Yahe & Chen, Zhe & Blaabjerg, Frede, 2024. "Bayesian averaging-enabled transfer learning method for probabilistic wind power forecasting of newly built wind farms," Applied Energy, Elsevier, vol. 355(C).
  13. 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.
  14. Liu, Tianhong & Qi, Shengli & Qiao, Xianzhu & Liu, Sixing, 2024. "A hybrid short-term wind power point-interval prediction model based on combination of improved preprocessing methods and entropy weighted GRU quantile regression network," Energy, Elsevier, vol. 288(C).
  15. Hongsheng Su & Yuwei Du & Yulong Che & Dan Li & Wenyao Su, 2025. "Hybrid Wind Power Forecasting for Turbine Clusters: Integrating Spatiotemporal WGANs with Extreme Missing-Data Resilience," Sustainability, MDPI, vol. 17(20), pages 1-18, October.
  16. Wang, Xiaodi & Hao, Yan & Yang, Wendong, 2024. "Novel wind power ensemble forecasting system based on mixed-frequency modeling and interpretable base model selection strategy," Energy, Elsevier, vol. 297(C).
  17. Xiao, Wenjing & Mo, Li & Xu, Zhanxing & Liu, Chang & Zhang, Yongchuan, 2024. "A hybrid electric load forecasting model based on decomposition considering fisher information," Applied Energy, Elsevier, vol. 364(C).
  18. Gou, Liangjie & Yang, Zhaozhong & Min, Chao & Yi, Duo & Li, Xiaogang & Kong, Bing, 2024. "A novel domain adaptation method with physical constraints for shale gas production forecasting," Applied Energy, Elsevier, vol. 371(C).
  19. 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).
  20. 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.
  21. Tian, Zhirui & Liu, Weican & Jiang, Wenqian & Wu, Chenye, 2024. "CNNs-Transformer based day-ahead probabilistic load forecasting for weekends with limited data availability," Energy, Elsevier, vol. 293(C).
  22. Wu, Binrong & Wang, Lin, 2024. "Two-stage decomposition and temporal fusion transformers for interpretable wind speed forecasting," Energy, Elsevier, vol. 288(C).
  23. Hussan, Umair & Wang, Huaizhi & Peng, Jianchun & Jiang, Hui & Rasheed, Hamna, 2026. "Transformer-based renewable energy forecasting: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 226(PC).
  24. 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).
  25. Gao, Huanxiang & Hu, Gang & Zhang, Dongqin & Jiang, Wenjun & Ren, Hehe & Chen, Wenli, 2024. "Prediction of wind fields in mountains at multiple elevations using deep learning models," Applied Energy, Elsevier, vol. 353(PA).
  26. Ullah, Sajid & Chen, Xi & Han, Han & Wu, Junhao & Dong, Jinghan & Liu, Ruiqing & Ding, Weijie & Liu, Min & Li, Qingli & Qi, Honggang & Huang, Yonggui & Yu, Philip Lh, 2025. "A novel hybrid ensemble approach for wind speed forecasting with dual-stage decomposition strategy using optimized GRU and transformer models," Energy, Elsevier, vol. 329(C).
  27. Verdone, Alessio & Panella, Massimo & De Santis, Enrico & Rizzi, Antonello, 2025. "A review of solar and wind energy forecasting: From single-site to multi-site paradigm," Applied Energy, Elsevier, vol. 392(C).
  28. 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).
  29. 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).
  30. 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).
  31. Ye, Xiaoling & Liu, Chengcheng & Xiong, Xiong & Qi, Yinyi, 2025. "Recurrent attention encoder–decoder network for multi-step interval wind power prediction," Energy, Elsevier, vol. 315(C).
  32. Wei, Xingchen & Wu, Xinyu & Yoshimura, Kei & Cheng, Chuntian & Huang, Hao & Ding, Zhendong & Song, Yuhang, 2025. "Climate-informed long-term forecasting of wind and photovoltaic power using a hybrid DWT–BES–CNN–LSTM model," Energy, Elsevier, vol. 338(C).
  33. Du, Pei & Yang, Dongchuan & Li, Yanzhao & Wang, Jianzhou, 2024. "An innovative interpretable combined learning model for wind speed forecasting," Applied Energy, Elsevier, vol. 358(C).
  34. Wang, Yun & Zhang, Fan & Kou, Hongbo & Zou, Runmin & Hu, Qinghua & Wang, Jianzhou & Srinivasan, Dipti, 2025. "A review of predictive uncertainty modeling techniques and evaluation metrics in probabilistic wind speed and wind power forecasting," Applied Energy, Elsevier, vol. 396(C).
  35. Liu, Yaru & Wang, Lei & Ng, Bing Feng, 2024. "A hybrid model-data-driven framework for inverse load identification of interval structures based on physics-informed neural network and improved Kalman filter algorithm," Applied Energy, Elsevier, vol. 359(C).
  36. 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).
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