Intelligent Models for Prediction of Compressive Strength of Geopolymer Pervious Concrete Hybridized with Agro-Industrial and Construction-Demolition Wastes
In modern civil engineering, precisely predicting the mechanical properties of waste-modified geopolymer concrete is a vital challenge. Machine learning (ML) offers a powerful tool for such predictive analysis. This article presents an experimental and python-based intelligent ML modeling study on a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-09-01
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| Series: | Studia Geotechnica et Mechanica |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/sgem-2024-0020 |