Data driven machine learning prognostics of buckling failure modes in ballasted railway track
Watcharapong Wongkaew,
Wachira Muanyoksakul,
Chayut Ngamkhanong
et al.
Abstract:This study explores the development and application of a machine learning (ML) approach to predict buckling failure modes in ballasted railway tracks. With the growing demand for safer and more reliable railway systems, the ability to foresee and mitigate track failures is of paramount importance. Our study focuses on harnessing advanced ML algorithms to analyse and interpret complex data sets, aiming to identify potential buckling failures before they occur. The methodology employed involves collecting extens… Show more
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