Comparative Analysis of Machine Learning Models for Predicting Interfacial Bond Strength of Fiber-Reinforced Polymer-Concrete

Comparative Analysis of Machine Learning Models for Predicting Interfacial Bond Strength of Fiber-Reinforced Polymer-Concrete

This study presents a detailed analysis of various machine learning models for predicting the interfacial bond strength of fiber-reinforced polymer (FRP) concrete, including multiple linear regression, Multigene Genetic Programming (MGGP), an ensemble of regression trees, Gaussian Process Regression...

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Bibliographic Details
Main Authors: Miljan Kovačević, Marijana Hadzima-Nyarko, Predrag Petronijević, Tatijana Vasiljević, Miroslav Radomirović
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Computation
Subjects:
fiber-reinforced polymer
bond strength
machine learning models
Online Access:https://www.mdpi.com/2079-3197/13/1/17
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