Title :
Radial basis function to predict scour depth around bridge abutment
Author :
Begum, Shahin Ara ; Fujail, Abul Kashim Md ; Barbhuiya, Abdul Karim
Author_Institution :
Dept. of Comput. Sci., Assam Univ., Silchar, India
Abstract :
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.
Keywords :
bridges (structures); condition monitoring; learning (artificial intelligence); radial basis function networks; structural engineering computing; bridge abutment; correlation coefficient; local scour depth prediction; mean absolute error; radial basis function network; root mean square error; Artificial neural networks; Bridges; Data models; Radial basis function networks; Sediments; Testing; Training; artificial neural network; radial basis function; scour depth prediction;
Conference_Titel :
Emerging Trends and Applications in Computer Science (NCETACS), 2011 2nd National Conference on
Conference_Location :
Shillong
Print_ISBN :
978-1-4244-9578-8
DOI :
10.1109/NCETACS.2011.5751387
