Robotics & Machine Learning Daily News2024,Issue(Jun.11) :122-123.

Data from VIT University Advance Knowledge in Support Vector Machines (Quantum s upport vector machine for forecasting house energy consumption: a comparative st udy with deep learning models)

VIT大学的数据支持向量机的高级知识(Quantum S支持向量机预测房屋能耗:与深度学习模型的比较研究)

Robotics & Machine Learning Daily News2024,Issue(Jun.11) :122-123.

Data from VIT University Advance Knowledge in Support Vector Machines (Quantum s upport vector machine for forecasting house energy consumption: a comparative st udy with deep learning models)

VIT大学的数据支持向量机的高级知识(Quantum S支持向量机预测房屋能耗:与深度学习模型的比较研究)

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摘要

由一名新闻记者兼机器人与机器学习每日新闻编辑-目前的研究结果已经公布。根据NewsRx记者在VIT大学的新闻报道,研究表明,“智能电网自动运行,促进了各种发电源顺利整合到电网中,从而确保了向最终用户持续、可靠和高质量的电力供应。智能电网应用领域的一个关键焦点是家庭能源管理系统(HEMS)。考虑到发电的波动性和加载条件的动态性,这具有重要意义。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on have been pub lished. According to news reporting from VIT University by NewsRx journalists, research stated, “The Smart Grid operates autonomously, facilitating the smooth i ntegration of diverse power generation sources into the grid, thereby ensuring a continuous, reliable, and high-quality supply of electricity to end users. One key focus within the realm of smart grid applications is the Home Energy Managem ent System (HEMS), which holds significant importance given the fluctuating avai lability of generation and the dynamic nature of loading conditions.”

Key words

VIT University/Emerging Technologies/M achine Learning/Support Vector Machines/Vector Machines

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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