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Natural language processing‐based deep transfer learning model across diverse tabular datasets for bond strength prediction of composite bars in concrete

Author(s): (State Key Laboratory of Ocean Engineering Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure School of Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China)
(State Key Laboratory of Ocean Engineering Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure School of Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China)
(Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Hong Kong China)
(State Key Laboratory of Ocean Engineering Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure School of Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China)
(State Key Laboratory of Ocean Engineering Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure School of Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China)
(State Key Laboratory of Ocean Engineering Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure School of Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai China)
(Department of Civil and Environmental Engineering The Hong Kong Polytechnic University Hong Kong China)
Medium: journal article
Language(s): English
Published in: Computer-Aided Civil and Infrastructure Engineering
DOI: 10.1111/mice.13357
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: 10.1111/mice.13357.
  • About this
    data sheet
  • Reference-ID
    10802055
  • Published on:
    10/11/2024
  • Last updated on:
    10/11/2024
 
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