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Urban wind field prediction based on sparse sensors and physics‐informed graph‐assisted auto‐encoder

Auteur(s): (Artificial Intelligence for Wind Engineering (AIWE) Lab, School of Civil and Environmental Engineering Harbin Institute of Technology Shenzhen China)
(Artificial Intelligence for Wind Engineering (AIWE) Lab, School of Civil and Environmental Engineering Harbin Institute of Technology Shenzhen China)
(Artificial Intelligence for Wind Engineering (AIWE) Lab, School of Civil and Environmental Engineering Harbin Institute of Technology Shenzhen China)
(Artificial Intelligence for Wind Engineering (AIWE) Lab, School of Civil and Environmental Engineering Harbin Institute of Technology Shenzhen China)
(Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon Hong Kong China)
(Centre for Wind, Waves and Water School of Civil Engineering The University of Sydney Sydney New South Wales Australia)
(NatHaz Modeling Laboratory University of Notre Dame Notre Dame Indiana USA)
Médium: article de revue
Langue(s): anglais
Publié dans: Computer-Aided Civil and Infrastructure Engineering, , n. 10, v. 39
DOI: 10.1111/mice.13147
Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.1111/mice.13147.
  • Informations
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  • Reference-ID
    10749647
  • Publié(e) le:
    14.01.2024
  • Modifié(e) le:
    05.05.2024
 
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