Advanced predictive machine and deep learning models for round-ended CFST column

Advanced predictive machine and deep learning models for round-ended CFST column

Abstract Confined columns, such as round-ended concrete-filled steel tubular (CFST) columns, are integral to modern infrastructure due to their high load-bearing capacity and structural efficiency. The primary objective of this study is to develop accurate, data-driven approaches for predicting the...

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Bibliographic Details
Main Authors: Feng Shen, Ishan Jha, Haytham F. Isleem, Walaa J.K. Almoghayer, Mohammad Khishe, Mohamed Kamel Elshaarawy
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Concrete-filled steel tubular columns
Axial load prediction
Machine learning models
Deep learning architectures
Structural engineering applications
SHAP Analysis
Online Access:https://doi.org/10.1038/s41598-025-90648-2
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https://doi.org/10.1038/s41598-025-90648-2

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