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Robust sparse Bayesian learning for broad learning with application to high-speed railway track monitoring

Auteur(s): ORCID (Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, China)
(Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, China)
ORCID (Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, China)
(China Railway Siyuan Survey and Design Group Co., Ltd, China)
(Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA)
ORCID (Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, China)
Médium: article de revue
Langue(s): anglais
Publié dans: Structural Health Monitoring, , n. 2, v. 22
Page(s): 147592172211042
DOI: 10.1177/14759217221104224
Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.1177/14759217221104224.
  • Informations
    sur cette fiche
  • Reference-ID
    10680459
  • Publié(e) le:
    18.06.2022
  • Modifié(e) le:
    21.03.2023
 
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