Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
A long term deflection response of reinforced concrete flexural members is influenced by many factors like compression reinforcement, creep coefficient, shrinkage strain, total time of experiment (years) and the ultimate compressive strength. A statistical approach artificial neural network for the predicting of long term deflection of reinforced concrete beams or slabs is proposed in this study. The artificial neural network predicted approach from this study was compared with (ACI-318) code equation. Results of artificial neural network was discussed and compared with the experimental data obtained from conducted studies. It showed a good agreement. However, the predicted approach was found to be too simplified to assess the increment of the long-term deflection.
How to cite this article:
Rana I. K. Zaki. Predicting the Long Term Deflection of Flexural Members
Using Artificial Neural Networks.
DOI: https://doi.org/10.36478/jeasci.2018.10039.10045
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.10039.10045