Explainable Data-Driven Ensemble Learning Models for the Mechanical Properties Prediction of Concrete Confined by Aramid Fiber-Reinforced Polymer Wraps Using Generative Adversarial Networks

Explainable Data-Driven Ensemble Learning Models for the Mechanical Properties Prediction of Concrete Confined by Aramid Fiber-Reinforced Polymer Wraps Using Generative Adversarial Networks

The current study offers a data-driven methodology to predict the ultimate strain and compressive strength of concrete reinforced by aramid FRP wraps. An experimental database was collected from the literature, on which seven different machine learning (ML) models were trained. The diameter and leng...

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Bibliographic Details
Main Author: Celal Cakiroglu
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Applied Sciences
Subjects:
aramid fiber reinforced polymers
machine learning
compressive strength
concrete confinement
XGBoost
SHAP
Online Access:https://www.mdpi.com/2076-3417/13/21/11991

Internet

https://www.mdpi.com/2076-3417/13/21/11991

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