Improved near surface wind speed predictions using Gaussian process regression combined with numerical weather predictions and observed meteorological data

Hoolohan, V, Tomlin, AS orcid.org/0000-0001-6621-9492 and Cockerill, T orcid.org/0000-0001-7914-2340 (2018) Improved near surface wind speed predictions using Gaussian process regression combined with numerical weather predictions and observed meteorological data. Renewable Energy, 126. pp. 1043-1054. ISSN 0960-1481

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 Elsevier Ltd. This is an author produced version of a paper published in Renewable Energy. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Gaussian process regression; Wind speed prediction; Atmospheric stability
Dates:
  • Published: October 2018
  • Accepted: 6 April 2018
  • Published (online): 7 April 2018
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Chemical & Process Engineering (Leeds)
The University of Leeds > Faculty of Engineering (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Thermofluids, Surfaces & Interfaces (iETSI) (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 09 Apr 2018 11:46
Last Modified: 07 Apr 2019 00:38
Status: Published
Publisher: Elsevier
Identification Number: https://doi.org/10.1016/j.renene.2018.04.019

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