Machine learning enhanced NARMAX model for Dst index forecasting

Gu, Y., Wei, H., Balikhin, M. et al. (2 more authors) (2019) Machine learning enhanced NARMAX model for Dst index forecasting. In: Proceedings of the 25th International Conference on Automation and Computing (ICAC). 25th International Conference on Automation and Computing (ICAC' 19), 05-07 Sep 2019, Lancaster, UK. IEEE . ISBN 9781728125183

Abstract

Metadata

Authors/Creators:
  • Gu, Y.
  • Wei, H.
  • Balikhin, M.
  • Boynton, R.
  • Walker, S.
Copyright, Publisher and Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.
Keywords: Magnetic Disturbance; Dst Index; NARMAX model; Machine Learning
Dates:
  • Accepted: 21 June 2019
  • Published (online): 11 November 2019
  • Published: 11 November 2019
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Funding Information:
FunderGrant number
Engineering and Physical Sciences Research Council (EPSRC)EP/I011056/1 and EP/H00453X/1
EU Horizon 2020637302
Depositing User: Symplectic Sheffield
Date Deposited: 17 Jul 2019 09:10
Last Modified: 23 Dec 2019 11:52
Status: Published
Publisher: IEEE
Refereed: Yes
Identification Number: https://doi.org/10.23919/IConAC.2019.8895027
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Filename: ICAC19 Machine Learning Enhanced NARMAX-1.pdf

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