Studies Conducted at University of Connecticut on Machine LearningRecently Repo rted (Assessing Grid Hardening Strategies To Improve Power System Performance Du ring Storms Using a Hybrid Mechanistic-machine Learning Outage Prediction Model)

Robotics & Machine Learning Daily News2024，Issue(Aug.7) ：89-90.

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Studies Conducted at University of Connecticut on Machine LearningRecently Repo rted (Assessing Grid Hardening Strategies To Improve Power System Performance Du ring Storms Using a Hybrid Mechanistic-machine Learning Outage Prediction Model)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news reportingoriginating from Storrs, Connectic ut, by NewsRx correspondents, research stated, “Improvements of powersystem per formance during severe weather events are targeted through grid hardening action s, such as strengthening aging infrastructure or performing vegetation managemen t. However, due to the complexityof modeling power system interactions with the environment and the impacts of proposed reinforcements,the benefits of such ha rdening actions are often unclear.”

Key words

Storrs/Connecticut/United States/Nort h and Central America/Cyborgs/Emerging Technologies/Machine Learning/Univers ity of Connecticut

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出版年

2024

Robotics & Machine Learning Daily News

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