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

fYear

2011

fDate

4-5 March 2011

Firstpage

1

Lastpage

7

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/NCETACS.2011.5751387

Filename

5751387