首页|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)
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)
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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.
DublinIrelandEuropeEmerging Techno logiesMachine LearningSupport Vector MachinesVector MachinesUniversity C ollege Dublin
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