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A new dam structural response estimation paradigm powered by deep learning and transfer learning techniques

Author(s): ORCID (State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China)
ORCID (State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China)
(State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China)
(State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China)
(State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China)
(School of Software Engineering, Tongji University, Shanghai, China)
(School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China)
Medium: journal article
Language(s): English
Published in: Structural Health Monitoring, , n. 3, v. 21
Page(s): 147592172110097
DOI: 10.1177/14759217211009780
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1177/14759217211009780.
  • About this
    data sheet
  • Reference-ID
    10608511
  • Published on:
    15/05/2021
  • Last updated on:
    09/05/2022
 
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