Chan_et_al_2021.pdf (1.65 MB)
Short Term Traffic Flow Prediction with Neighbor Selecting Gated Recurrent Unit
conference contribution
posted on 2023-08-30, 20:01 authored by Yin-Hei Chan, Andrew Kwok-Fai Lui, Sin-Chun NgTraffic 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.
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Page range
857-862ISSN
2577-1655External DOI
Publisher
IEEEPlace of publication
OnlineISBN
978-1-6654-4207-7Conference 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, AustraliaEvent start date
2021-10-17Event finish date
2021-10-20File version
- Accepted version
Language
- eng
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Legacy posted date
2022-06-09Legacy creation date
2022-06-09Legacy Faculty/School/Department
Faculty of Science & EngineeringUsage metrics
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