Development of user-friendly kernel-based Gaussian process regression model for prediction of load-bearing capacity of square concrete-filled steel tubular members
TT Le, MV Le - Materials and Structures, 2021 - Springer
Abstract A Machine Learning (ML) model based on Gaussian regression, using different
kernel functions, is introduced in this paper to assess the load-carrying capacity of square …
kernel functions, is introduced in this paper to assess the load-carrying capacity of square …
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 …
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 …
A hybrid machine learning approach in prediction and uncertainty quantification of ultimate compressive strength of RCFST columns
MST Nguyen, SE Kim - Construction and Building Materials, 2021 - Elsevier
This article introduces a machine learning-based approach to estimate the ultimate
compressive strength of rectangular concrete-filled steel tube (RCFST) columns, and to …
compressive strength of rectangular concrete-filled steel tube (RCFST) columns, and to …
Surrogate neural network model for prediction of load-bearing capacity of CFSS members considering loading eccentricity
TT Le - Applied Sciences, 2020 - mdpi.com
In this study, a surrogate Machine Learning (ML)-based model was developed, to predict the
load-bearing capacity (LBC) of concrete-filled steel square hollow section (CFSS) members …
load-bearing capacity (LBC) of concrete-filled steel square hollow section (CFSS) members …
Machine learning (ML) based models for predicting the ultimate strength of rectangular concrete-filled steel tube (CFST) columns under eccentric loading
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 …
accurate prediction of their ultimate strength is a key for the safety of the structure. Extensive …
Uncertainty quantification of ultimate compressive strength of CCFST columns using hybrid machine learning model
MST Nguyen, MC Trinh, SE Kim - Engineering with Computers, 2022 - Springer
This study aims to estimate the value and quantify the uncertainty of the compressive
strength of circular concrete-filled steel tube (CCFST) columns under eccentric loading using …
strength of circular concrete-filled steel tube (CCFST) columns under eccentric loading using …
Practical Hybrid Machine Learning Approach for Estimation of Ultimate Load of Elliptical Concrete‐Filled Steel Tubular Columns under Axial Loading
TT Le - Advances in civil engineering, 2020 - Wiley Online Library
In this study, a hybrid machine learning (ML) technique was proposed to predict the bearing
capacity of elliptical CFST columns under axial load. The proposed model was Adaptive …
capacity of elliptical CFST columns under axial load. The proposed model was Adaptive …
Optimization and modeling of axial strength of concrete-filled double skin steel tubular columns using response surface and neural-network methods
The main objective of this study is to optimize and model the ultimate strength of axially
loaded concrete-filled double skin steel tubular (CFDST) composite columns having a …
loaded concrete-filled double skin steel tubular (CFDST) composite columns having a …
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 …