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Computers and Concrete Volume 11, Number 3, March 2013 , pages 237-252 DOI: https://doi.org/10.12989/cac.2013.11.3.237 |
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Application of artificial neural networks (ANNs) and linear regressions (LR) to predict the deflection of concrete deep beams |
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Mohammad Mohammadhassani, Hossein Nezamabadi-pour,
Mohd Zamin Jumaat, Mohammed Jameel and Arul M S Arumugam
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| Abstract | ||
| This paper presents the application of artificial neural network (ANN) to predict deep beam deflection using experimental data from eight high-strength-self-compacting-concrete (HSSCC) deep beams. The optimized network architecture was ten input parameters, two hidden layers, and one output. The feed forward back propagation neural network of ten and four neurons in first and second hidden layers using TRAINLM training function predicted highly accurate and more precise load-deflection diagrams compared to classical linear regression (LR). The ANN | ||
| Key Words | ||
| deflection; deep beams; artificial neural network; high strength self compacting concrete; linear regression | ||
| Address | ||
| Mohammad Mohammadhassani: Department of Civil Engineering, University of Malaya, Malaysia; Hossein Nezamabadi-pour: Department of Electrical Engineering, Shahid Bahonar University of Kerman-Iran; Mohd Zamin Jumaat, Mohammed Jameel and Arul M S Arumugam: Department of Civil Engineering, University of Malaya, Malaysia | ||