首页|Researchers at Department of Electrical and Electronics Engineering Zero in on M achine Learning (Machine Learning Models for Predicting and Managing Electric Ve hicle Load in Smart Grids)

Researchers at Department of Electrical and Electronics Engineering Zero in on M achine Learning (Machine Learning Models for Predicting and Managing Electric Ve hicle Load in Smart Grids)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news originating from the Department of El ectrical and Electronics Engineering by NewsRx correspondents, research stated, “The integration of electric vehicles (EVs) into smart grids provides major issu es and prospects for effective energy management.” The news reporters obtained a quote from the research from Department of Electri cal and Electronics Engineering: “This research examines the actual utilization of machine learning models to forecast and manage EV demand in smart grids, inte nded to increase grid effectiveness and dependable operation. We acquire and pre process different datasets, considering elements such as time of usage, characte ristics of the environment, and user behaviors. Multiple machine learning models , combining neural networks, support vector machines, and forests that are rando m, are developed and rated for their projected accuracy. Our results imply that enhanced prediction algorithms may considerably raise all the level of detail of EV load forecasts. Furthermore, we recommend load management systems based on r eal-time forecasts to enhance energy distribution and lower peak demand.”

Department of Electrical and Electronics EngineeringCyborgsEmerging TechnologiesMachine Learning

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Oct.16)