Application of Neural Networks for the Estimation of the Shear Strength of Circular RC Columns

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.