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421-430 trong số 1397 kết quả
Weighting Justice Reform Costs and Benefits Using Machine Learning and Modern Data Science
Tác giả: Chris Mahony
Xuất bản: World Bank, Washington, DC , 2023
Bộ sưu tập: Tài liệu truy cập mở
ddc:  006.31
 
Machine Learning Reduced Order Model for Cost and Emission Assessment of a Pyrolysis System [electronic resource]
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2021
Bộ sưu tập: Báo, Tạp chí
ddc:  621.47
 
Machine learning to predict biomass sorghum yields under future climate scenarios [electronic resource]
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Dept. of Energy. Office of Science ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2020
Bộ sưu tập: Báo, Tạp chí
ddc: 
 
Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2 [electronic resource]
Tác giả:
Xuất bản: Oak Ridge, Tenn. : Oak Ridge, Tenn: Oak Ridge National Laboratory ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2021
Bộ sưu tập: Báo, Tạp chí
ddc:  610.28
 
DDxNet [electronic resource] : a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. National Nuclear Security Administration ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2020
Bộ sưu tập: Báo, Tạp chí
ddc:  616.12
 
Utilizing physics-based input features within a machine learning model to predict wind speed forecasting error [electronic resource]
Tác giả:
Xuất bản: Richland, Wash. : Oak Ridge, Tenn: Pacific Northwest National Laboratory (U.S.) ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2021
Bộ sưu tập: Báo, Tạp chí
ddc:  333.9
 
How accurate is a machine learning-based wind speed extrapolation under a round-robin approach? [electronic resource]
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2020
Bộ sưu tập: Báo, Tạp chí
ddc:  621.531
 
The importance of round-robin validation when assessing machine-learning-based vertical extrapolation of wind speeds [electronic resource]
Tác giả:
Xuất bản: Washington, D.C. : Oak Ridge, Tenn: United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy , 2020
Bộ sưu tập: Báo, Tạp chí
ddc:  621.531
 
Inferential Theory for Granular Instrumental Variables in High Dimensions
Tác giả: Saman Banafti, Tae-Hwy Lee
Xuất bản: , 2022
Bộ sưu tập: Báo, Tạp chí
eBook (pdf)
ddc:  511.4
 
Who Increases Emergency Department Use? New Insights from the Oregon Health Insurance Experiment
Tác giả: Augustine Denteh, Helge Liebert
Xuất bản: , 2022
Bộ sưu tập: Báo, Tạp chí
eBook (pdf)
ddc:  174.936334
 

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