Quantifying the Effect of Lidar Turbulence Error on Wind Power Prediction [electronic resource]
	Tác giả:
	Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2016
	Bộ sưu tập: Metadata
	ddc:  621.45  Thêm vào giỏ

Learning curves for drug response prediction in cancer cell lines [electronic resource]
	Tác giả:
	Xuất bản: Washington DC Oak Ridge Tenn: United States Dept of Energy Office of Science Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2021
	Bộ sưu tập: Metadata
	ddc:  577.3  Thêm vào giỏ

The Power Curve Working Group's assessment of wind turbine power performance prediction methods [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:  621.45  Thêm vào giỏ

Generating wind power scenarios for probabilistic ramp event prediction using multivariate statistical post-processing [electronic resource]
	Tác giả:
	Xuất bản: Golden Colo Oak Ridge Tenn: National Renewable Energy Laboratory US Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2018
	Bộ sưu tập: Metadata
	ddc:  333.79  Thêm vào giỏ

Validating the MFiX-DEM Model for Flow Regime Prediction in a 3D Spouted Bed [electronic resource]
	Tác giả:
	Xuất bản: Washington DC Oak Ridge Tenn: United States Office of the Assistant Secretary of Energy for Fossil Energy Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2018
	Bộ sưu tập: Metadata
	ddc:  622.7  Thêm vào giỏ

Validating the MFiX-DEM Model for Flow Regime Prediction in a 3D Spouted Bed [electronic resource]
	Tác giả:
	Xuất bản: Washington DC Oak Ridge Tenn: United States Office of the Assistant Secretary of Energy for Fossil Energy Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2018
	Bộ sưu tập: Metadata
	ddc:  622.33  Thêm vào giỏ

Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning [electronic resource]
	Tác giả:
	Xuất bản: Washington DC Oak Ridge Tenn: United States National Nuclear Security Administration Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2020
	Bộ sưu tập: Metadata
	ddc:  621.5  Thêm vào giỏ

The effect of model fidelity on prediction of char burnout for single-particle coal combustion [electronic resource]
	Tác giả:
	Xuất bản: Washington DC Oak Ridge Tenn: United States National Nuclear Security Administration Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2016
	Bộ sưu tập: Metadata
	ddc:  621.4  Thêm vào giỏ

Reliability and Lifetime Prediction Model of Sintered Silver under High-Temperature Cycling [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:  553.8  Thêm vào giỏ

The use of real-time off-site observations as a methodology for increasing forecast skill in prediction of large wind power ramps one or more hours ahead of their impact on a wind plant. [electronic
	Tác giả:
	Xuất bản: Oak Ridge Tenn: Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2012
	Bộ sưu tập: Metadata
	ddc:  621.5  Thêm vào giỏ