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The Newcastle University research output collection, currently available on ePrints, will shortly be moving to a new open repository platform, Figshare. To prepare for the data migration we have paused adding new content to ePrints, and will resume once the new repository is launched. During this time you will continue to have access to ePrints (but no new content will appear). We will share updates here when available.

A machine learning approach to appraise and enhance the structural resilience of buildings to seismic hazards

Lookup NU author(s): Dr Wanqing ZhaoORCiD

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Licence

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Publication metadata

Author(s): Cere G, Rezgui Y, Zhao W, Petri I

Publication type: Article

Publication status: Published

Journal: Structures

Year: 2022

Volume: 45

Pages: 1516-1529

Print publication date: 01/11/2022

Online publication date: 06/10/2022

Acceptance date: 28/09/2022

Date deposited: 12/12/2024

ISSN (electronic): 2352-0124

Publisher: Elsevier Ltd

URL: https://doi.org/10.1016/j.istruc.2022.09.113

DOI: 10.1016/j.istruc.2022.09.113


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Funding

Funder referenceFunder name
Building Research Establishment (BRE)
Natural Environment Research Council (NERC): NE/N012240/1

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