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A novel data-driven bridge monitoring data prediction framework using improved intelligent optimization-assisted deep learning

Auteur(s): ORCID (School of Civil Engineering and Architecture, East China Jiao Tong University, Nanchang, People’s Republic of China)
(School of Civil Engineering and Architecture, East China Jiao Tong University, Nanchang, People’s Republic of China)
(Key Laboratory of Concrete and Prestressed Concrete Structure of Ministry of Education, Southeast University, Nanjing, People’s Republic of China)
ORCID (School of Civil Engineering and Architecture, East China Jiao Tong University, Nanchang, People’s Republic of China)
ORCID (Key Laboratory of Concrete and Prestressed Concrete Structure of Ministry of Education, Southeast University, Nanjing, People’s Republic of China)
(School of Civil Engineering and Architecture, East China Jiao Tong University, Nanchang, People’s Republic of China)
Médium: article de revue
Langue(s): anglais
Publié dans: Structural Health Monitoring
DOI: 10.1177/14759217241305598
Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.1177/14759217241305598.
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  • Reference-ID
    10812111
  • Publié(e) le:
    17.01.2025
  • Modifié(e) le:
    17.01.2025
 
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