Enhancement of Unsteady and 3D Aerodynamics Models using Machine Learning [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

Implementing Machine Learning in the PCWG Tool [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:  621.45  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

How Generalizable is a Machine-Learning Approach for Modeling Hub-Height Turbulence Intensity? [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, 2022
	Bộ sưu tập: Metadata
	ddc:  621.531  Thêm vào giỏ

How accurate is a machine learning-based wind speed extrapolation under a round-robin 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, 2020
	Bộ sưu tập: Metadata
	ddc:  621.531  Thêm vào giỏ

Machine learning to predict biomass sorghum yields under future climate scenarios [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, 2020
	Bộ sưu tập: Metadata
	ddc:   Thêm vào giỏ

Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning [electronic resource] : A Methodological Approach
	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, 2020
	Bộ sưu tập: Metadata
	ddc:  623.2  Thêm vào giỏ

Using Machine Learning to Create Turbine Performance Models (Presentation) [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, 2013
	Bộ sưu tập: Metadata
	ddc:  621.521  Thêm vào giỏ

Ubiquitous Traffic Volume Estimation through Machine Learning Procedure [electronic resource]
	Tác giả:
	Xuất bản: Washington DC Oak Ridge Tenn: United States Office of the Assistant Secretary of Energy Efficiency and Renewable Energy Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2019
	Bộ sưu tập: Metadata
	ddc:  621.39  Thêm vào giỏ

A Machine-Learning Decision-Support Tool for Travel-Demand Modeling [electronic resource]
	Tác giả:
	Xuất bản: Washington DC Oak Ridge Tenn: United States Office of the Assistant Secretary of Energy Efficiency and Renewable Energy Distributed by the Office of Scientific and Technical Information US Dept of Energy, 2019
	Bộ sưu tập: Metadata
	ddc:  629.2  Thêm vào giỏ