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1 Ergebnisse
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Wind power prediction method based on CNN-LSTM-Attention an..:
, In:
2024 IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)
,
Zhu, Zhuangwei
;
Jiang, Jing
;
Zhu, Xiaolong
.. - p. 1683-1690 , 2024
Link:
https://doi.org/10.1109/IMCEC59810.2024.10575340
RT T1
2024 IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)
: T1
Wind power prediction method based on CNN-LSTM-Attention and Bayesian optimization
UL https://suche.suub.uni-bremen.de/peid=ieee-10575340&Exemplar=1&LAN=DE A1 Zhu, Zhuangwei A1 Jiang, Jing A1 Zhu, Xiaolong A1 Zheng, Guang A1 Zhan, Zhiming YR 2024 SN 2693-2776 K1 Accuracy K1 Time series analysis K1 Wind power generation K1 Predictive models K1 Wind farms K1 Feature extraction K1 Convolutional neural networks K1 wind power prediction K1 convolutional neural network K1 long short-term memory network K1 attention mechanism K1 bayesian optimization SP 1683 OP 1690 LK http://dx.doi.org/https://doi.org/10.1109/IMCEC59810.2024.10575340 DO https://doi.org/10.1109/IMCEC59810.2024.10575340 SF ELIB - SuUB Bremen
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