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Short Term Traffic Flow Prediction with Neighbor Selecting Gated Recurrent Unit

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conference contribution
posted on 2023-08-30, 20:01 authored by Yin-Hei Chan, Andrew Kwok-Fai Lui, Sin-Chun Ng
Traffic flow prediction is an important component of a modern intelligent transport system. Building an effective model for short term traffic flow prediction model is challenging. Traffic is spatial temporal in nature. A traffic flow prediction model should consider an appropriate scope of neighbourhood of traffic. To address the needs of a dynamic scope of neighbourhood. We introduce a novel gated recurrent unit variant call Neighbor Selecting Gated Recurrent Unit(NSGRU). NSGRU feature a learn-able spatial kernel with distance based K-nearest neighbor trimming scheme. Embedded external traffic knowledge are used to aid with the learning of spatial kernel. The NSGRU was evaluated with a quantized real world dataset and observed consistent improvement over baseline models.

History

Page range

857-862

ISSN

2577-1655

Publisher

IEEE

Place of publication

Online

ISBN

978-1-6654-4207-7

Conference proceeding

2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Name of event

2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Location

Melbourne, Australia

Event start date

2021-10-17

Event finish date

2021-10-20

File version

  • Accepted version

Language

  • eng

Legacy posted date

2022-06-09

Legacy creation date

2022-06-09

Legacy Faculty/School/Department

Faculty of Science & Engineering

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