Short-term Wind Power Prediction Based on CEEMDAN De-composition and Spatiotemporal Feature Fusion
| Autor(en): |
Xingchen Guo
(School of Electrical Engineering, Xi'an University of Technology, Xi'an, China)
Rong Jia (School of Electrical Engineering, Xi'an University of Technology, Xi'an, China) Gang Zhang (School of Electrical Engineering, Xi'an University of Technology, Xi'an, China) Benben Xu (School of Electrical Engineering, Xi'an University of Technology, Xi'an, China) Xin He (School of Electrical Engineering, Xi'an University of Technology, Xi'an, China) |
|---|---|
| Medium: | Fachartikel |
| Sprache(n): | Englisch |
| Veröffentlicht in: | Proceedings of the Institution of Civil Engineers - Energy, November 2022, n. 4, v. 175 |
| Seite(n): | 1-27 |
| DOI: | 10.1680/jener.21.00104 |
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Datenseite - Reference-ID
10665203 - Veröffentlicht am:
09.05.2022 - Geändert am:
10.12.2022
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