Integration of support vector regression and grey wolf optimization for estimating the ultimate bearing capacity in concrete-filled steel tube columns

NT Ngo, HA Le, TPT Pham - Neural Computing and Applications, 2021 - Springer
Concrete-filled steel tube (CFST) columns are widely used in the construction industry.
Prediction of the ultimate bearing capacity of CFST columns is complicated because it is …

Prediction of bearing capacity of the square concrete-filled steel tube columns: An application of metaheuristic-based neural network models

P Sarir, DJ Armaghani, H Jiang, MMS Sabri, B He… - Materials, 2022 - mdpi.com
During design and construction of buildings, the employed materials can substantially
impact the structures' performance. In composite columns, the properties and performance of …

PCA-based hybrid intelligence models for estimating the ultimate bearing capacity of axially loaded concrete-filled steel tubes

K Khan, R Biswas, J Gudainiyan, MN Amin, HJ Qureshi… - Materials, 2022 - mdpi.com
In order to forecast the axial load-carrying capacity of concrete-filled steel tubular (CFST)
columns using principal component analysis (PCA), this work compares hybrid models of …

Research on axial bearing capacity of rectangular concrete-filled steel tubular columns based on artificial neural networks

Y Du, Z Chen, C Zhang, X Cao - Frontiers of Computer Science, 2017 - Springer
Abstract Design of rectangular concrete-filled steel tubular (CFT) columns has been a big
concern owing to their complex constraint mechanism. Generally, most existing methods are …

Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns

P Sarir, J Chen, PG Asteris, DJ Armaghani… - Engineering with …, 2021 - Springer
The type of materials used in designing and constructing structures significantly affects the
way the structures behave. The performance of concrete and steel, which are used as a …

Predicting compressive strength of RCFST columns under different loading scenarios using machine learning optimization

F Wu, F Tang, R Lu, M Cheng - Scientific Reports, 2023 - nature.com
Accurate bearing capacity assessment under load conditions is essential for the design of
concrete-filled steel tube (CFST) columns. This paper presents an optimization-based …

Optimum model for bearing capacity of concrete-steel columns with AI technology via incorporating the algorithms of IWO and ABC

P Sarir, SL Shen, ZF Wang, J Chen… - Engineering with …, 2021 - Springer
In a composite column, the performance of both the concrete and steel has a considerable
effect on the structural behaviour under different loading conditions. This study applies …

Axial compression prediction and GUI design for CCFST column using machine learning and shapley additive explanation

X Liu, Y Wu, Y Zhou - Buildings, 2022 - mdpi.com
Axial bearing capacity is the key index of circular concrete-filled steel tubes (CCFST). A
hybrid PSO-ANN model consisting of an artificial neural network (ANN) optimized with …

[HTML][HTML] Artificial neural network assisted bearing capacity and confining pressure prediction for rectangular concrete-filled steel tube (CFT)

B Zhao, P Li, Y Du, Y Li, X Rong, X Zhang… - Alexandria Engineering …, 2023 - Elsevier
The evaluation of the confining pressure between steel and concrete is a complex yet
important issue for concrete-filled steel tube (CFT) columns. The previous study is mainly …

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 …