Predicting hourly boarding demand of bus passengers using imbalanced records from smart-cards: A deep learning approach

Tang, T, Liu, R orcid.org/0000-0003-0627-3184, Choudhury, C orcid.org/0000-0002-8886-8976 et al. (2 more authors) (2023) Predicting hourly boarding demand of bus passengers using imbalanced records from smart-cards: A deep learning approach. IEEE Transactions on Intelligent Transportation Systems, 24 (5). pp. 5105-5119. ISSN 1524-9050

Abstract

Metadata

Item Type: Article
Authors/Creators:
Keywords: Boarding behaviour prediction; smart-card; bus; data imbalance issue; deep generative adversarial network; deep neural network
Dates:
  • Published: May 2023
  • Published (online): 23 January 2023
  • Accepted: 22 September 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Choice Modelling
The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds)
Funding Information:
Funder
Grant number
RCUK (Research Councils UK)
MR/T020423/1
Depositing User: Symplectic Publications
Date Deposited: 11 Oct 2022 08:52
Last Modified: 16 May 2023 11:54
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Identification Number: 10.1109/TITS.2023.3237134
Open Archives Initiative ID (OAI ID):

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