where researchers studied the use of data coming from a P2D PBM to train different ML algorithms like decision trees (DTs), random forests (RFs), and gradient boosted machines (GBMs). This research highlights the use of these models for time critical applications, since introducing ML can increase execution times while keeping a high accuracy for predicting discharge profiles.