Advanced Machine Learning Modeling Approach for Prediction of Compressive Strength of FRP Confined Concrete Using Multiphysics Genetic Expression Programming

Advanced Machine Learning Modeling Approach for Prediction of Compressive Strength of FRP Confined Concrete Using Multiphysics Genetic Expression Programming

The purpose of this article is to demonstrate the potential of gene expression programming (GEP) in anticipating the compressive strength of circular CFRP confined concrete columns. A new GEP model has been developed based on a credible and extensive database of 828 data points to date. Numerous ana...

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Bibliographic Details
Main Authors: Israr Ilyas, Adeel Zafar, Muhammad Talal Afzal, Muhammad Faisal Javed, Raid Alrowais, Fadi Althoey, Abdeliazim Mustafa Mohamed, Abdullah Mohamed, Nikolai Ivanovich Vatin
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Polymers
Subjects:
CFRP
modelling
machine learning
GEP
strength model
confinement
Online Access:https://www.mdpi.com/2073-4360/14/9/1789

Internet

https://www.mdpi.com/2073-4360/14/9/1789

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