Compressive strength of nano concrete materials under elevated temperatures using machine learning

Compressive strength of nano concrete materials under elevated temperatures using machine learning

Abstract In this study, four Artificial intelligence (AI) - based machine learning models were developed to estimate the Residual compressive strength (RCS) value of concrete supported with nano additives of Nanocarbon tubes (NCTs) and Nano alumina (NAl), after exposure to elevated temperatures rang...

Full description

Saved in:
Bibliographic Details
Main Authors: Abdullah M. Zeyad, Alaa A. Mahmoud, Alaa A. El-Sayed, Ayman M. Aboraya, Islam N. Fathy, Nikos Zygouris, Panagiotis G. Asteris, Ibrahim Saad Agwa
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Series:Scientific Reports
Subjects:
Machine learning
Elevated temperature
Nano additives
Artificial neural networks
Fuzzy logic models
Genetic algorithms
Online Access:https://doi.org/10.1038/s41598-024-73713-0
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items