Findings from China Earthquake Administration Yields New Data on Support Vector Machines [Cumulative Absolute Velocity (Cav) Parameter Estima tion In Earthquake Emergency Response Based On a Support Vector Machine]

中国地震局的调查结果为支持向量机提供了新的数据[基于支持向量机的地震应急响应累积绝对速度(Cav)参数估计]

Robotics & Machine Learning Daily News2024，Issue(Jul.3) ：5-6.

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Findings from China Earthquake Administration Yields New Data on Support Vector Machines [Cumulative Absolute Velocity (Cav) Parameter Estima tion In Earthquake Emergency Response Based On a Support Vector Machine]

中国地震局的调查结果为支持向量机提供了新的数据[基于支持向量机的地震应急响应累积绝对速度(Cav)参数估计]

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摘要

一位新闻记者兼机器人与机器学习的新闻编辑每日新闻-在一份新的报告中讨论了支持向量机的研究结果。根据NewsRx记者来自中华人民共和国哈尔滨的新闻报道，研究表明，"快速准确地估计地震期间的应急响应参数对于地震预警(EEW)系统非常重要"。本研究的资金来源包括中国地震局工程力学研究所科研基金、国家自然科学基金(NSFC)、中国铁路科学股份有限公司科研基金项目。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Support Vector Ma chines are discussed in a new report. According to news reporting originating fr om Harbin, People’s Republic of China, by NewsRx correspondents, research stated , “Rapid and accurate estimation of emergency response parameters during earthqu akes is important in earthquake early warning (EEW) systems.” Financial supporters for this research include Scientific Research Fund of Insti tute of Engineering Mechanics, China Earthquake Administration, National Natural Science Foundation of China (NSFC), R &D Fund Project of China Acad emy of Railway Science Corporation Limited.

Key words

Harbin/People's Republic of China/Asia/Emerging Technologies/Machine Learning/Support Vector Machines/Vector Machi nes/China Earthquake Administration

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出版年

2024

Robotics & Machine Learning Daily News

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