Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
This study compares Bayesian Optimization-based machine learning systems that anticipate earthquake-damaged buildings and to evaluates building damage classification models. Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. This study showed damage level as...
| Auteurs principaux: | , , , , , |
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| Format: | Article |
| Publié: |
Springer Cham
2024
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