Machine learning model for building seismic peak roof drift ratio assessment

Machine learning model for building seismic peak roof drift ratio assessment

AbstractThe peak roof drift ratio is one of the most important engineering parameters to describe the expected seismic damage in a building. A predictive model of the drift ratio was developed using a machine learning approach (Gaussian process regression model) on a dataset of approximately 11,800...

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Bibliographic Details
Main Authors: Federico Mori, Daniele Spina, Flavio Bocchi, Amerigo Mendicelli, Giuseppe Naso, Massimiliano Moscatelli
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
Seismic risk mitigation
machine learning
Gaussian process regression model
building roof drift ratio
regional scale
Online Access:https://www.tandfonline.com/doi/10.1080/19475705.2023.2182658

Internet

https://www.tandfonline.com/doi/10.1080/19475705.2023.2182658

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