Application of Neural Networks for the Estimation of
the Shear Strength of Circular RC Columns
Authors: Viet Chuong - Ho; Thi Quynh - Nguyen; Tien Hong- Nguyen; Duy Duan - Nguyen
Engineering, Technology & Applied Science Research
: 12(6) : 9409-9413
Publishing year: 12/2022
Abstract-This study aims to develop Artificial Neural Networks
(ANNs) for predicting the shear strength of circular Reinforced
Concrete (RC) columns. A set of 156 experimental data samples
of various circular RC columns were utilized to establish the
ANN model. The performance results of the ANN model show
that it predicts the shear strength of circular RC columns
accurately with a high coefficient of determination (0.99) and a
small root-mean-square error (4.6kN). The result comparison
reveals that the proposed ANN model can predict the shear
strength of the columns more accurately than the existing
equations. Moreover, an ANN-based formula is proposed to
explicitly calculate the shear strength of the columns.
Additionally, a practical Graphical User Interface (GUI) tool is
developed for facilitating the practical design process of the
circular RC columns.
Keywords-artificial neural networks; circular reinforced concrete column; graphical user interface; shear strength
