Predicting track quality using structural elements and relative track geometry data measured by RILA: A Machine Learning Classification approach

Track quality measures differ from standard to standard. Widely used indices for track quality are the standard deviations of the rail longitudinal level data and the standard deviations of alignment data. Researchers have opted for various learning methods as to relate track quality to different parameters. Some research has gone to the point...