Computational Technology Resources - CCP

S. Radovanovic^1,2, V. Milivojevic², V. Cirovic², D. Divac² and N. Milivojevic²

¹Faculty of Civil Engineering, University of Belgrade, Serbia
²Institute for the Development of Water Resources "Jaroslav Cerni", Belgrade, Serbia

doi:10.4203/ccp.109.20

purchase the full-text of this paper

S. Radovanovic, V. Milivojevic, V. Cirovic, D. Divac, N. Milivojevic, "Prediction of Concrete Dam Deformation using Artificial Neural Networks", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 20, 2015. doi:10.4203/ccp.109.20

Keywords: dam, deformation, artificial neural network, prediction, temperature, water level, multiple linear regression.

Summary

The goal of this paper is to assess the effectiveness of using artificial neural networks in the prediction of concrete dam deformation. The aging of dams as a concrete structures poses a significant risk for the environment, and many of them are at the stage where it is necessary to pay attention to their behaviour. Short-term term prediction of deformation is very important for rapid response in the case of any adverse events. Two examples are presented in this paper to investigate how short-term prediction of deformation can be realized by using artificial neural networks. As a comparison, a set of statistical linear regression models are established using the same data. The conclusions on the basis of the analysis and the established models are presented. The paper provides an assessment of the network structure and a comparison of neural network models for the usual concept of statistical models for the monitoring of dams.

purchase the full-text of this paper (price £20)

go to the previous paper
go to the next paper
return to the table of contents
return to the book description
purchase this book (price £50 +P&P)

	Computational & Technology Resources an online resource for computational, engineering & technology publications
	not logged in - login
Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 109 PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON SOFT COMPUTING TECHNOLOGY IN CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING Edited by: Y. Tsompanakis, J. Kruis and B.H.V. Topping Paper 20 Prediction of Concrete Dam Deformation using Artificial Neural Networks S. Radovanovic^1,2, V. Milivojevic², V. Cirovic², D. Divac² and N. Milivojevic² ¹Faculty of Civil Engineering, University of Belgrade, Serbia ²Institute for the Development of Water Resources "Jaroslav Cerni", Belgrade, Serbia doi:10.4203/ccp.109.20 purchase the full-text of this paper Full Bibliographic Reference for this paper S. Radovanovic, V. Milivojevic, V. Cirovic, D. Divac, N. Milivojevic, "Prediction of Concrete Dam Deformation using Artificial Neural Networks", in Y. Tsompanakis, J. Kruis, B.H.V. Topping, (Editors), "Proceedings of the Fourth International Conference on Soft Computing Technology in Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 20, 2015. doi:10.4203/ccp.109.20 Keywords: dam, deformation, artificial neural network, prediction, temperature, water level, multiple linear regression. Summary The goal of this paper is to assess the effectiveness of using artificial neural networks in the prediction of concrete dam deformation. The aging of dams as a concrete structures poses a significant risk for the environment, and many of them are at the stage where it is necessary to pay attention to their behaviour. Short-term term prediction of deformation is very important for rapid response in the case of any adverse events. Two examples are presented in this paper to investigate how short-term prediction of deformation can be realized by using artificial neural networks. As a comparison, a set of statistical linear regression models are established using the same data. The conclusions on the basis of the analysis and the established models are presented. The paper provides an assessment of the network structure and a comparison of neural network models for the usual concept of statistical models for the monitoring of dams. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £50 +P&P)
Back to top	©Civil-Comp Limited 2023 - terms & conditions