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Equation-driven strength prediction of GGBS concrete: a symbolic machine learning approach for sustainable development Cover

Equation-driven strength prediction of GGBS concrete: a symbolic machine learning approach for sustainable development

REVIEWS ON ADVANCED MATERIALS SCIENCE
Volume 64 (2025): Issue 1 (January 2025)
By: Muhammad Nasir Amin,  Asad Naeem,  Muhammad Iftikhar Faraz and  Muhammad Tahir Qadir  
Open Access
|Dec 2025
DOI: https://doi.org/10.1515/rams-2025-0183 | Journal eISSN: 1605-8127
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Language: English
Submitted on: Aug 14, 2025
Accepted on: Oct 31, 2025
Published on: Dec 11, 2025
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Keywords:
ground granulated blast-furnace slag-based concrete,
compressive strength,
machine learning prediction models
Related subjects:
Chemistry,
Chemistry, other,
Engineering,
Introductions and overviews,
Engineering, other,
Materials sciences,
Porous materials,
Physics,
Physics, other

© 2025 Muhammad Nasir Amin, Asad Naeem, Muhammad Iftikhar Faraz, Muhammad Tahir Qadir, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 License.

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