Machine learning for better prediction of seepage flow through embankment dams: Gaussian process regression versus SVR and RVM.

In the present study, three machine learning methods were applied for predicting seepage flow through embankment dams, namely (i) support vector regression (SVR), relevance vector machine (RVM), and Gaussian process regression (GPR). The three models were developed using seepage flow (Q: L/mn) and piezometer level (Z:m) measured at several piezometers placed in the corps body of the dam. The proposed models were calibrated and validated using a separate subset.