A novel multi-layer stacking ensemble wind power prediction model under Tensorflow deep learning framework considering feature enhancement and data hierarchy processing
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DOI: 10.1016/j.energy.2023.129409
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Cited by:
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- Zhong, Mingwei & Fan, Jingmin & Luo, Jianqiang & Xiao, Xuanyi & He, Guanglin & Cai, Rui, 2024. "InfoCAVB-MemoryFormer: Forecasting of wind and photovoltaic power through the interaction of data reconstruction and data augmentation," Applied Energy, Elsevier, vol. 371(C).
- Wang, Zheng & Peng, Tian & Zhang, Xuedong & Chen, Jialei & Qian, Shijie & Zhang, Chu, 2025. "Enhancing multi-step short-term solar radiation forecasting based on optimized generalized regularized extreme learning machine and multi-scale Gaussian data augmentation technique," Applied Energy, Elsevier, vol. 377(PD).
- Meng, Anbo & Zhang, Haitao & Dai, Zhongfu & Xian, Zikang & Xiao, Liexi & Rong, Jiayu & Li, Chen & Zhu, Jianbin & Li, Hanhong & Yin, Yiding & Liu, Jiawei & Tang, Yanshu & Zhang, Bin & Yin, Hao, 2024. "An adaptive distribution-matched recurrent network for wind power prediction using time-series distribution period division," Energy, Elsevier, vol. 299(C).
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Keywords
Wind power prediction; Ensemble learning; DBSCAN; Feature enhancement; Data hierarchy processing;All these keywords.
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