Machine learning-driven optimization for predicting compressive strength in fly ash geopolymer concrete
This study employs machine learning (ML) techniques to predict the compressive strength (fc′) of fly ash-based geopolymer concrete, utilizing a comprehensive set of experimental data. The analysis considered variables such as fly ash (FA) components, coarse and fine aggregates, alkaline activator mo...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Cleaner Engineering and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666790825000229 |
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