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 |
---|---|
格式: | 文件 |
出版: |
Springer Cham
2024
|
相似书籍
-
Evaluation and prediction of time overruns in Jordanian construction projects using coral reefs optimization and deep learning methods
由: Shihadeh, Jumana, et al.
出版: (2024) -
Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
由: almahameed, Bader aldeen, et al.
出版: (2024) -
Bayesian network for earthquake damage risk modeling and management
由: Tao, Yihui
出版: (2018) -
Repair of buildings damaged by earthquakes/
由: United Nations. Department of Economic and Social Affairs
出版: (1977) -
Classification of Heavily Damaged Building Damage after Earthquake
由: Varol Koç
出版: (2016-03-01)