Robotics & Machine Learning Daily News2024,Issue(Nov.20) :85-86.

New Machine Learning Study Findings Reported from Army Engineering University (M achine Learning-based Vhf Lightning Radiation Sources Identification)

陆军工程大学机器学习研究新发现(基于机器学习的甚高频雷电辐射源识别)

Robotics & Machine Learning Daily News2024,Issue(Nov.20) :85-86.

New Machine Learning Study Findings Reported from Army Engineering University (M achine Learning-based Vhf Lightning Radiation Sources Identification)

陆军工程大学机器学习研究新发现(基于机器学习的甚高频雷电辐射源识别)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-关于机器学习的最新研究结果已经发表。据新闻报道《中国人民日报》南京报道,NewsRx编辑,研究称,“识别”定位结果的有效性是雷电辐射源测绘的一个重要步骤,可以为雷电辐射源测绘提供参考消除了噪声定位结果的干扰,保留了real辐射源,获得了清晰、准确的定位结果连续闪电通道发展图。定位方法,如电磁时间反演和多重信号分类具有较高的定位精度,但其有效性验证它们的定位结果依赖于主观设定的阈值,这使得它们难以准确区分弱辐射源和噪声的定位结果。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Current study results on Machine Learn ing have been published. According to newsreporting out of Nanjing, People’s Re public of China, by NewsRx editors, research stated, “Identifyingthe validity o f the location result is an important step in lightning radiation source mapping , which caneliminate the interference of noise location results, retain the rea l radiation source, and obtain a clear andcontinuous lightning channel developm ent map. The localization methods, such as electromagnetic timereversal and mul tiple signal classification have high location accuracy, but the validity identi fication oftheir location result depends on the subjectively set threshold, whi ch makes it hard to accurately distinguishthe location results of weak radiatio n source and noise.”

Key words

Nanjing/People’s Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning/Army Engineering University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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