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1 Ergebnisse
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Probabilistic forecasts of wind power generation in regions..:
Foldvik Eikeland, Odin
;
Hovem, Finn Dag
;
Olsen, Tom Eirik
..
Eikeland, O.F. (2023). Enhancing Decision-making in the Electric Power Sector with Machine Learning and Optimization. (Doctoral thesis). https://hdl.handle.net/10037/31514 .. , 2022
Link:
https://hdl.handle.net/10037/27600
RT Journal T1 <Title>Probabilistic forecasts of wind power generation in regions with complex topography using deep learning methods: An Arctic case</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftunivtroemsoe:oai:munin.uit.no:10037_27600&Exemplar=1&LAN=DE A1 Foldvik Eikeland, Odin A1 Hovem, Finn Dag A1 Olsen, Tom Eirik A1 Chiesa, Matteo A1 Bianchi, Filippo Maria PB Elsevier YR 2022 K1 VDP::Teknologi: 500::Miljøteknologi: 610 K1 VDP::Technology: 500::Environmental engineering: 610 K1 Deep learning / Deep learning K1 Energidataanalyse / Energy analytics K1 Vindkraft / Wind power JF Eikeland, O.F. (2023). Enhancing Decision-making in the Electric Power Sector with Machine Learning and Optimization. (Doctoral thesis). https://hdl.handle.net/10037/31514 . LK http://dx.doi.org/https://hdl.handle.net/10037/27600 DO https://hdl.handle.net/10037/27600 SF ELIB - SuUB Bremen
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