Application of machine learning techniques to predict the compressive strength of steel fiber reinforced concrete

Application of machine learning techniques to predict the compressive strength of steel fiber reinforced concrete

Abstract The accurate prediction of compressive strength (CS) in steel fiber reinforced concrete (SFRC) remains a critical challenge due to the material’s inherent complexity and the nonlinear interactions among its constituents. This study presents a robust machine learning framework to predict the...

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Bibliographic Details
Main Authors: Ala’a R. Al-Shamasneh, Arsalan Mahmoodzadeh, Faten Khalid Karim, Taoufik Saidani, Abdulaziz Alghamdi, Jasim Alnahas, Mohammed Sulaiman
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Steel fiber reinforced concrete
Compressive strength
Data analysis
Machine learning
Feature importance
Online Access:https://doi.org/10.1038/s41598-025-16516-1
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