A Machine Learning Model to Predict the Seismic Lifecycle Behavior of a Cross-Sea Cable-Stayed Bridg...
A Machine Learning Model to Predict the Seismic Lifecycle Behavior of a Cross-Sea Cable-Stayed Bridge
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Publisher
Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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Contents
Cross-sea cable-stayed bridges encounter challenges associated with cable corrosion and cable-force relaxation during their service life, which significantly affects their structural performance and seismic response. This study focuses on a cross-sea cable-stayed bridge located in Hainan Province. Utilizing an LSTM deep learning model, this study a...
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Full title
A Machine Learning Model to Predict the Seismic Lifecycle Behavior of a Cross-Sea Cable-Stayed Bridge
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TN_cdi_doaj_primary_oai_doaj_org_article_ecb9485c91a54575ae1e346df7594736
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_ecb9485c91a54575ae1e346df7594736
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ISSN
2075-5309
E-ISSN
2075-5309
DOI
10.3390/buildings14051190
