Learning congestion propagation behaviors for traffic prediction
Traffic prediction is a challenging task as the traffic flow is influenced by many seasonal, stochastic, and structural factors. In addition, the spatial and temporal distribution of traffic flow can induce direct and indirect congestion propagation patterns. While existing works have attempted to model s...
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Main Authors: | , , , |
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Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2021
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/153857 |
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Institution: | Nanyang Technological University |
Language: | English |