Short-term traffic prediction with vicinity Gaussian process in the presence of missing data

Wang, P., Kim, Y., Vaci, L. et al. (2 more authors) (2018) Short-term traffic prediction with vicinity Gaussian process in the presence of missing data. In: 2018 Sensor Data Fusion: Trends, Solutions, Applications (SDF). 12th Symposium Sensor Data Fusion: Trends, Solutions, and Applications, 09-11 Oct 2018, Bonn, Germany. IEEE ISBN 978-1-5386-9398-8

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
  • Wang, P.
  • Kim, Y.
  • Vaci, L.
  • Yang, H.
  • Mihaylova, L.S.
Copyright, Publisher and Additional Information:

© 2018 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.

Dates:
  • Published: 29 November 2018
  • Published (online): 29 November 2018
  • Accepted: 10 September 2018
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:
Funder
Grant number
EUROPEAN COMMISSION - HORIZON 2020
688082
Depositing User: Symplectic Sheffield
Date Deposited: 25 Sep 2018 10:21
Last Modified: 30 Jan 2019 16:29
Published Version: https://doi.org/10.1109/SDF.2018.8547118
Status: Published
Publisher: IEEE
Refereed: Yes
Identification Number: 10.1109/SDF.2018.8547118
Open Archives Initiative ID (OAI ID):

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