Passenger Behavior Prediction With Semantic and Multi-Pattern LSTM Model

Passenger Behavior Prediction With Semantic and Multi-Pattern LSTM Model

Understanding passenger behaviors is of great importance in intelligent transportation and infrastructure planning. However, the passenger trajectories are actually complex temporal data, which consist of rich spatial and temporal information. What's more, the observed passenger trajectories ma...

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Bibliographic Details
Main Authors: Haiquan Wang, Xin Wu, Leilei Sun, Bowen Du
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Behavioral sciences
big data applications
predictive models
public transportation
Online Access:https://ieeexplore.ieee.org/document/8889510/

Internet

https://ieeexplore.ieee.org/document/8889510/

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