Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning-Reference-Cited by-同舟云学术

Hierarchical Bayesian modeling for knowledge transfer across engineering fleets via multitask learning

Published:2022-08-08 Issue:7 Volume:38 Page:821-848
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer aided Civil Eng

Author:

Bull L. A.¹,Di Francesco D.¹,Dhada M.²,Steinert O.³,Lindgren T.⁴,Parlikad A. K.²,Duncan A. B.¹⁵,Girolami M.¹⁶

Affiliation:

1. The Alan Turing Institute The British Library London UK

2. Institute for Manufacturing, Department of Engineering University of Cambridge Cambridge UK

3. Strategic Product Planning and Advanced Analytics Scania CV, Scania AB (publ) Södertälje Sweden

4. Department of Computer and Systems Sciences Stockholm University Kista Sweden

5. Department of Mathematics Imperial College London London UK

6. Department of Engineering University of Cambridge Cambridge UK

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering,Building and Construction

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12901

Reference69 articles.

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2. A novel methodology for modal parameters identification of large smart structures using MUSIC, empirical wavelet transform, and Hilbert transform

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