Integrating machine learning and symbolic regression for predicting damage initiation in hybrid FRP bolted connections

Integrating machine learning and symbolic regression for predicting damage initiation in hybrid FRP bolted connections

Abstract The increasing adoption of machine learning (ML) in fiber-reinforced polymer (FRP) composite design has led to a reliance on black-box models, which achieve high predictive accuracy but lack interpretability. Python symbolic regression (PySR) offers a solution by deriving explicit equations...

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Bibliographic Details
Main Authors: Sherif Samy Sorour, Chahinaz Abdelrahman Saleh, Mostafa Shazly
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Machine learning
Symbolic regression
PySR
Bolted connections
Laminated FRP composites
Online Access:https://doi.org/10.1038/s41598-025-02390-4
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https://doi.org/10.1038/s41598-025-02390-4

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