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...
| Main Authors: | Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza |
|---|---|
| Format: | Article |
| Published: |
Springer Cham
2024
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/105841/ |
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