Robotics & Machine Learning Daily News2024,Issue(Jan.8) :40-40.

Researchers at University of Connecticut Release New Data on Machine Learning (Probabilistic Physics-informed Graph Convolutional Network for Active Distribution System Voltage Prediction)

Robotics & Machine Learning Daily News2024,Issue(Jan.8) :40-40.

Researchers at University of Connecticut Release New Data on Machine Learning (Probabilistic Physics-informed Graph Convolutional Network for Active Distribution System Voltage Prediction)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Machine Learning. According to news reportingfrom Storrs, Connecticut, by NewsRx journalists, research stated, “This letter proposes a novel data-drivenprobabilistic physics-informed graph convolutional network (GCN) for active distribution system voltageprediction with PVs and EVs. It leverages both measurements and network topology to accurately andefficiently predict node voltages without the need for an accurate distribution system power flow model.”Funders for this research include United States Department of Energy (DOE), United States Departmentof Energy (DOE).

Key words

Storrs/Connecticut/United States/North and Central America/Cyborgs/Emerging Technologies/Machine Learning/University of Connecticut

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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