A machine-learning-based model for predicting the effective stiffness of precast concrete columns

Machine learning method is firstly used to systematically study the ES of PCCs. A database is assembled including 177 flexural-dominant PCCs with 42 features. A VEL model with feature selection is proposed to predict the ES of PCCs. The VEL model is experimentally verified and compared with empirical formulas. The VEL model is interpreted using the combination of PDA and ICE.