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The importance of round-robin validation when assessing machine-learning-based vertical extrapolation of wind speeds [electronic resource]
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Energy Efficiency and Renewable Energy Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2020
Bộ sưu tập: Metadata
ddc:  621.531
 
New methods to improve the vertical extrapolation of near-surface offshore wind speeds [electronic resource]
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Energy Efficiency and Renewable Energy Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2021
Bộ sưu tập: Metadata
ddc:  621.45
 
Quantifying sensitivity in numerical weather prediction-modeled offshore wind speeds through an ensemble modeling approach [electronic resource]
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Energy Efficiency and Renewable Energy Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2021
Bộ sưu tập: Metadata
ddc:  621.5
 
Sensitivity of turbine-height wind speeds to parameters in planetary boundary-layer and surface-layer schemes in the weather research and forecasting model [electronic resource]
Tác giả:
Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Energy Efficiency and Renewable Energy Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2016
Bộ sưu tập: Metadata
ddc:  621.531
 
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