Prediction of the load-shortening curve of CFST columns using ANN-based models
M Zarringol, HT Thai - Journal of Building Engineering, 2022 - Elsevier
Artificial neural network (ANN) as a machine learning (ML) technique has been successfully
applied in engineering applications such as structural dynamics and structural design. It has …
applied in engineering applications such as structural dynamics and structural design. It has …
Application of ANN to the design of CFST columns
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 …
rectangular and circular concrete-filled steel tubular (CFST) columns subjected to concentric …
Prediction of axial load capacity of rectangular concrete-filled steel tube columns using machine learning techniques
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 …
rectangular concrete-filled steel tubular (CFST) columns based on soft computing …
Improving the axial compression capacity prediction of elliptical CFST columns using a hybrid ANN-IP model
This study proposes a new and highly-accurate artificial intelligence model, namely ANN-IP,
which combines an interior-point (IP) algorithm and artificial neural network (ANN), to …
which combines an interior-point (IP) algorithm and artificial neural network (ANN), to …
Strength prediction of circular CFST columns through advanced machine learning methods
C Hou, XG Zhou - Journal of Building Engineering, 2022 - Elsevier
Concrete-filled steel tube (CFST), well recognized for its excellent mechanical behaviour
and economic efficiency, is widely used as a main load-carrying component in various kinds …
and economic efficiency, is widely used as a main load-carrying component in various kinds …
Optimized data-driven machine learning models for axial strength prediction of rectangular CFST columns
XG Zhou, C Hou, WQ Feng - Structures, 2023 - Elsevier
The nonlinear material interaction in concrete-filled steel tube (CFST) significantly
contributes to its excellent axial compression behaviour, which in the meantime results in …
contributes to its excellent axial compression behaviour, which in the meantime results in …
Practical machine learning-based prediction model for axial capacity of square CFST columns
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 …
Regression (GPR) was developed to predict the axial load of square concrete-filled steel …
Application of machine learning models for designing CFCFST columns
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 …
(SVR) and artificial neural network (ANN) are employed to predict the ultimate strength of …
Novel ensemble approach to predict the ultimate axial load of CFST columns with different cross-sections
Concrete-filled steel tubes (CFST) have been widely used in construction due to their
numerous benefits over traditional structural components made of steel or reinforced …
numerous benefits over traditional structural components made of steel or reinforced …
Explainable machine learning models for predicting the axial compression capacity of concrete filled steel tubular columns
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 …
due to enhanced mechanical properties such as higher strength and ductility, higher seismic …