A neat approach to structural health monitoring

Tsialiamanis, G., Wagg, D.J., Dervilis, N. orcid.org/0000-0002-5712-7323 et al. (1 more author) (2020) A neat approach to structural health monitoring. In: Papadrakakis, M., Fragiadakis, M. and Papadimitriou, C., (eds.) EURODYN 2020: Proceedings of the XI International Conference on Structural Dynamics. EURODYN 2020: XI International Conference on Structural Dynamics, 23-26 Nov 2020, Athens, Greece. European Association for Structural Dynamics (EASD) , pp. 3832-3845. ISBN 9786188507227

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 The Authors. This is an author-produced version of a paper subsequently published in EURODYN 2020 Proceedings.
Keywords: Structural health monitoring; machine learning; neural networks; neuroevolution of augmenting topologies (NEAT)
Dates:
  • Published: 30 September 2020
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Funding Information:
FunderGrant number
European Commission - HORIZON 2020764547
Depositing User: Symplectic Sheffield
Date Deposited: 19 Feb 2021 13:00
Last Modified: 19 Feb 2021 16:24
Status: Published
Publisher: European Association for Structural Dynamics (EASD)
Refereed: Yes
Identification Number: https://doi.org/10.47964/1120.9313.19022
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