Prediction of Autogenous Shrinkage of Concrete Incorporating Super Absorbent Polymer and Waste Materials through Individual and Ensemble Machine Learning Approaches

Prediction of Autogenous Shrinkage of Concrete Incorporating Super Absorbent Polymer and Waste Materials through Individual and Ensemble Machine Learning Approaches

The use of superabsorbent polymers, sometimes known as SAP, is a tremendously efficacious method for reducing the amount of autogenous shrinkage (AS) that occurs in high-performance concrete. This study utilizes support vector regression (SVR) as a standalone machine-learning algorithm (MLA) which i...

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Bibliographic Details
Main Authors: Hisham Jahangir Qureshi, Muhammad Umair Saleem, Muhammad Faisal Javed, Abdulrahman Fahad Al Fuhaid, Jawad Ahmad, Muhammad Nasir Amin, Kaffayatullah Khan, Fahid Aslam, Md Arifuzzaman
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Materials
Subjects:
concrete
materials
autogenous shrinkage
super absorbent Polymer
machine learning approaches
ensemble models
Online Access:https://www.mdpi.com/1996-1944/15/21/7412

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https://www.mdpi.com/1996-1944/15/21/7412

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