Prediction of the axial compression capacity of stub CFST columns using machine learning techniques
K Megahed, NS Mahmoud, SEM Abd-Rabou - Scientific Reports, 2024 - nature.com
Concrete-filled steel tubular (CFST) columns have extensive applications in structural
engineering due to their exceptional load-bearing capability and ductility. However, existing …
engineering due to their exceptional load-bearing capability and ductility. However, existing …
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 …
Application of machine learning models in the capacity prediction of RCFST columns
K Megahed, NS Mahmoud, SEM Abd-Rabou - Scientific Reports, 2023 - nature.com
Rectangular concrete-filled steel tubular (RCFST) columns are widely used in structural
engineering due to their excellent load-carrying capacity and ductility. However, existing …
engineering due to their excellent load-carrying capacity and ductility. However, existing …
Predicting axial load capacity of CFST columns using machine learning
I Faridmehr, ML Nehdi - Structural Concrete, 2022 - Wiley Online Library
Owing to their economic and structural advantages, concrete‐filled steel tubular (CFST)
columns have been implemented in diverse structural applications, especially in high‐rise …
columns have been implemented in diverse structural applications, especially in high‐rise …
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 …
Machine learning applications to predict the axial compression capacity of concrete filled steel tubular columns: a systematic review
Purpose This study seeks to understand the connection of methodology by finding relevant
papers and their full review using the “Preferred Reporting Items for Systematic Reviews and …
papers and their full review using the “Preferred Reporting Items for Systematic Reviews and …
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 …
Machine learning-based prediction of CFST columns using gradient tree boosting algorithm
Among recent artificial intelligence techniques, machine learning (ML) has gained
significant attention during the past decade as an emerging topic in civil and structural …
significant attention during the past decade as an emerging topic in civil and structural …
Universal boosting ML approaches to predict the ultimate load capacity of CFST columns
TA Nguyen, K Le Nguyen, HB Ly - The Structural Design of Tall …, 2024 - Wiley Online Library
Establishing a universal machine learning (ML) model in structural engineering is vital for
understanding how various parameters, like geometry and material properties, influence a …
understanding how various parameters, like geometry and material properties, influence a …