2024 Volume 5 Issue 1 Pages 43-55
In order to improve the quality of maintenance management against scouring disasters, which threaten the safety and stability of railroad transportation, it is necessary to evaluate the risk of localized scouring at the piers of railroad river bridges and to identify river bridges with a high possibility of being damaged. To this end, a database was constructed by collecting and organizing conditions related to river characteristics and bridge structures from past cases of excavation damage and unaffected cases. We also attempted to construct a learning model that determines whether a bridge is damaged or not by using a decision tree algorithm, which is one of machine learning models, on the database. The prediction results obtained from the learning model were compared with the evaluation scores from the scour scoring table, and the usefulness of the machine learning model was verified.
