Comparison of machine learning models to forecast shear strength of reinforced concrete walls

Abstract

This research focuses on developing and comparing single and ensemble machine learning models to predict the shear strength of reinforced concrete walls. Four single models ANN, SVR, LR, CART and three ensemble models Voting, Bagging, Stacking are bulit to solve this issue. The analysis results show that the ANN model in the ensemble Bagging model has higher accuracy than other methods mentioned in the literature.

Keywords: Reinforced concrete, shear capacity; machine learning model; optimization; Jellyfish search optimizer.