TY - JOUR
T1 - Estimation of structural response using convolutional neural network
T2 - application to the Suramadu bridge
AU - Pamuncak, Arya Panji
AU - Salami, Mohammad Reza
AU - Adha, Augusta
AU - Budiono, Bambang
AU - Laory, Irwanda
N1 - Funding Information:
This study is funded by the British Council (Grant ID: 217544274), and Indonesian Endowment Fund for Education (PRJ-589/LPDP.3/2017 and S-2160/LPDP.4/2019). The writers would also like to acknowledge the support from the Indonesian Ministry of Public Works and Housing (IMPWH) and the University of Warwick, UK. Any opinions, findings and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the IMPWH.
Publisher Copyright:
© 2021, Emerald Publishing Limited.
PY - 2021
Y1 - 2021
KW - Cable force
KW - Cable-stayed bridge
KW - Convolutional neural networks
KW - Data-based interpretation
KW - Structural health monitoring
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U2 - 10.1108/EC-12-2020-0695
DO - 10.1108/EC-12-2020-0695
M3 - Article
AN - SCOPUS:85106282630
SN - 0264-4401
VL - 38
SP - 4047
EP - 4065
JO - Engineering Computations (Swansea, Wales)
JF - Engineering Computations (Swansea, Wales)
IS - 10
ER -