Computers and Concrete

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On successive machine learning process for predicting strength and displacement of rectangular reinforced concrete columns subjected to cyclic loading

  • Bu-seog Ju (Department of Civil Engineering, Kyung Hee University) ;
  • Shinyoung Kwag (Department of Civil and Environmental Engineering, Hanbat National University) ;
  • Sangwoo Lee (Department of Civil Engineering, Kyung Hee University)
  • Received : 2023.05.09
  • Accepted : 2023.07.07
  • Published : 2023.11.25
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Abstract

Recently, research on predicting the behavior of reinforced concrete (RC) columns using machine learning methods has been actively conducted. However, most studies have focused on predicting the ultimate strength of RC columns using a regression algorithm. Therefore, this study develops a successive machine learning process for predicting multiple nonlinear behaviors of rectangular RC columns. This process consists of three stages: single machine learning, bagging ensemble, and stacking ensemble. In the case of strength prediction, sufficient prediction accuracy is confirmed even in the first stage. In the case of displacement, although sufficient accuracy is not achieved in the first and second stages, the stacking ensemble model in the third stage performs better than the machine learning models in the first and second stages. In addition, the performance of the final prediction models is verified by comparing the backbone curves and hysteresis loops obtained from predicted outputs with actual experimental data.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT). (No.2021R1A2C1010278).

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