Robotics & Machine Learning Daily News2024,Issue(Jul.2) :116-117.

Findings from University College Dublin in the Area of Support Vector Machines R eported (An Unsupervised Anomaly Detection Framework for Onboard Monitoring of R ailway Track Geometrical Defects Using One-class Support Vector Machine)

都柏林大学学院在支持向量机领域的研究结果(一种基于单类支持向量机的轨道几何缺陷车载监测无监督异常检测框架)

Robotics & Machine Learning Daily News2024,Issue(Jul.2) :116-117.

Findings from University College Dublin in the Area of Support Vector Machines R eported (An Unsupervised Anomaly Detection Framework for Onboard Monitoring of R ailway Track Geometrical Defects Using One-class Support Vector Machine)

都柏林大学学院在支持向量机领域的研究结果(一种基于单类支持向量机的轨道几何缺陷车载监测无监督异常检测框架)

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摘要

由一名新闻记者-机器人与机器学习每日新闻编辑-调查人员发布了关于支持向量机的新报告。根据Ne wsRx编辑在爱尔兰都柏林的新闻报道,研究表明:“轨道几何是铁路轨道状况的关键指标之一,需要长期持续监测和维护,本文提出了一种基于人工智能(AI)的铁路轨道几何检测框架k,利用从专用测量高速列车采集的振动数据进行轨道几何检测。”这项研究的财政支持来自爱尔兰科学基金会。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Su pport Vector Machines. According to news reporting out of Dublin, Ireland, by Ne wsRx editors, research stated, “Track geometry is one of the critical indicators of railway tracks’ condition which requires continuous monitoring and maintenan ce over time. In this paper, a novel artificial intelligence (AI) based framewor k is proposed for railway track geometry inspection using vibration data collect ed from a dedicated measuring high-speed train.” Financial support for this research came from Science Foundation Ireland.

Key words

Dublin/Ireland/Europe/Emerging Techno logies/Machine Learning/Support Vector Machines/Vector Machines/University C ollege Dublin

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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