The nonlinear material interaction in concrete-filled steel tube (CFST) significantly contributes to its excellent axial compression behaviour, which in the meantime results in …
C Wang, TM Chan - Engineering Structures, 2023 - Elsevier
Concrete-filled steel tubes (CFSTs) are popularly used in structural applications. The accurate prediction of their ultimate strength is a key for the safety of the structure. Extensive …
TT Le - Mechanics of Advanced Materials and Structures, 2022 - Taylor & Francis
In this paper, a surrogate Machine-Learning (ML) model based on Gaussian Process Regression (GPR) was developed to predict the axial load of square concrete-filled steel …
Among recent artificial intelligence techniques, machine learning (ML) has gained significant attention during the past decade as an emerging topic in civil and structural …
M Zarringol, HT Thai, MZ Naser - Journal of Constructional Steel Research, 2021 - Elsevier
In this study, two machine learning (ML) algorithms including support vector regression (SVR) and artificial neural network (ANN) are employed to predict the ultimate strength of …
This work aims to develop a novel and practical equation for predicting the axial load of rectangular concrete-filled steel tubular (CFST) columns based on soft computing …
Concrete-filled steel tubular (CFST) columns have been popular in the construction industry due to enhanced mechanical properties such as higher strength and ductility, higher seismic …
The literature on predicting the load-carrying capacity of symmetrical concrete-filled steel tube (Sy-CFST) columns using different machine learning methods has mainly focused on a …
M Zarringol, HT Thai, S Thai, V Patel - Structures, 2020 - Elsevier
In this paper, artificial neural network (ANN) is used to predict the ultimate strength of rectangular and circular concrete-filled steel tubular (CFST) columns subjected to concentric …