Meta databases of steel frame buildings for surrogate modelling and machine learning-based feature importance analysis

Meta databases of steel frame buildings for surrogate modelling and machine learning-based feature importance analysis

Traditionally, nonlinear time history analysis (NLTHA) is used to assess the performance of structures under future hazards which is necessary to develop effective disaster risk management strategies. However, this method is computationally intensive and not suitable for analyzing a large number of...

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Bibliographic Details
Main Authors: Delbaz Samadian, Imrose B. Muhit, Annalisa Occhipinti, Nashwan Dawood
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Resilient Cities and Structures
Subjects:
Surrogate models
Meta database
Pushover analysis
Steel moment resisting frames
Sensitivity and explainability analyses
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2772741623000716

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http://www.sciencedirect.com/science/article/pii/S2772741623000716

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