This application aims to provide a friendly environment for bridge enginners to evluate the scour risk in an accurate yet rapid way. Data used in this study was provided by the French National Rialway Company (SNCF).
Detailed information of this study may refer to the following papers, which are currently under review and in preparation :
- Wang, T., Reiffsteck, P., Chevalier, C., Zhu, Z., Schmidt, F., (2022). A novel extreme gradient boosting algorithm based model for predicting the scour risk around bridge piers : application to French railway bridges predicting the scour risk around bridge piers : application to. European Journal of Environmental and Civil Engineering, https://doi.org/10.1080/19648189.2022.2072957
- Wang T., Reiffsteck P., Chevalier C., Chen C., Schmidt F. An interpretable framework for bridge scour based on explainable artificial intelligence (XAI)