Predicting the Temperature Regime in Hardening Massive Monolithic Walls Using CatBoost Gradient Boosting
Thermal cracking due to hydration heat in massive monolithic walls poses a significant risk, but traditional prediction methods are often too complex for rapid engineering assessments. This study aims to develop machine learning models to predict the maximum temperature and center-to-surface tempera...
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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2026-06-01
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| Serie: | Buildings |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2075-5309/16/12/2287 |
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