Radial basis function to predict scour depth around bridge abutment

Local scour around bridge abutment is a time-dependent complex phenomenon encountered world-wide. It is difficult to establish a general empirical model that can be applied to all abutment conditions. In this paper, Radial basis function (RBF) Network has been used to predict the maximum scour depth around bridge abutment. An appropriate model is identified using experimental data from literature. The efficiency of the developed model has been evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Correlation Coefficient (CC). Experimental results show the suitability and reliability of the application of Artificial Neural Network for scour depth prediction around bridge abutments.