Application of ANN in predicting ACC of SCFST column
The main objective of this paper is to derive a new empirical formula for predicting the axial
compression capacity (ACC) of square concrete-filled steel tubular (SCFST) columns using …
compression capacity (ACC) of square concrete-filled steel tubular (SCFST) columns using …
A hybrid model for predicting the axial compression capacity of square concrete-filled steel tubular columns
Accurate prediction of axial compression capacity (ACC) of concrete-filled steel tubular
(CFST) columns is an important issue to maintain the safety levels of related structures and …
(CFST) columns is an important issue to maintain the safety levels of related structures and …
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 …
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 …
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 …
Efficiency of three advanced data-driven models for predicting axial compression capacity of CFDST columns
VL Tran, SE Kim - Thin-Walled Structures, 2020 - Elsevier
This study aims to investigate the performance of three advanced data-driven models,
namely multivariate adaptive regression spline (MARS), artificial neural network (ANN), and …
namely multivariate adaptive regression spline (MARS), artificial neural network (ANN), and …
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 …
A comprehensive and reliable investigation of axial capacity of Sy-CFST columns using machine learning-based models
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 …
tube (Sy-CFST) columns using different machine learning methods has mainly focused on a …
Ultimate capacity prediction of axially loaded CFST short columns
EM Güneyisi, A Gültekin, K Mermerdaş - International Journal of Steel …, 2016 - Springer
Composite columns have superior strength and ductility performance, and they have
become more widely accepted in the engineering applications. However, the filled tubular …
become more widely accepted in the engineering applications. However, the filled tubular …
Predicting the ultimate axial capacity of uniaxially loaded cfst columns using multiphysics artificial intelligence
The object of this research is concrete-filled steel tubes (CFST). The article aimed to develop
a prediction Multiphysics model for the circular CFST column by using the Artificial Neural …
a prediction Multiphysics model for the circular CFST column by using the Artificial Neural …