Techno Press
Techno Press

Computers and Concrete
  Volume 32, Number 5, November 2023 , pages 513-525
DOI: https://doi.org/10.12989/cac.2023.32.5.513
 


On successive machine learning process for predicting strength and displacement of rectangular reinforced concrete columns subjected to cyclic loading
Bu-seog Ju, Shinyoung Kwag and Sangwoo Lee

 
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.
 
Key Words
    bagging; ensemble machine learning; multiple-input multiple-output; reinforced concrete column; stacking
 
Address
Bu-seog Ju and Sangwoo Lee: Department of Civil Engineering, Kyung Hee University, Yongin-Si, Gyeonggi-Do, Republic of Korea
Shinyoung Kwag: Department of Civil and Environmental Engineering, Hanbat National University, Daejeon Republic of Korea
 

Techno-Press: Publishers of international journals and conference proceedings.       Copyright © 2026 Techno Press
P.O. Box 33, Yuseong, Daejeon 305-600 Korea, Tel: +82-42-828-7996, Fax : +82-42-828-7997, Email: admin@techno-press.com