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A machine learning approach to the prediction of tidal currents

Abstract:

We propose the use of techniques from Machine Learning for the prediction of tidal currents. The classical methodology of harmonic analysis is widely used in the prediction of tidal currents and computer algorithms based on the method have been used for decades for the purpose. The approach determines parameters by minimizing the difference between the raw data and model output using the least squares optimization approach. However, although the approach is considered to be state-of-the-art, ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Publisher:
International Society of Offshore and Polar Engineers
Host title:
The Proceedings of the 26th International Ocean and Polar Engineering Conference, Rhodes, Greece, June 26-July 1, 2016
Journal:
26th International Ocean and Polar Engineering Conference More from this journal
Volume:
1
Pages:
692-700
Publication date:
2016-01-01
Acceptance date:
2016-03-24
ISSN:
1098-6189
ISBN:
9781880653883
Pubs id:
pubs:614683
UUID:
uuid:1f633375-eb37-423e-9099-c623382543f1
Local pid:
pubs:614683
Source identifiers:
614683
Deposit date:
2016-04-09

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