Spatial-temporal deep learning model based on Similarity Principle for dock shared bicycles ridership prediction

Spatial-temporal deep learning model based on Similarity Principle for dock shared bicycles ridership prediction

Demand prediction plays a critical role in traffic research. The key challenge of traffic demand prediction lies in modeling the complex spatial dependencies and temporal dynamics. However, there is no mature and widely accepted concept to support the solution of the above challenge. Essentially,  ...

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Bibliographic Details
Main Authors: Jiahui Zhao, Zhibin Li, Pan Liu, Mingye Zhang
Format: Article
Language:English
Published: University of Minnesota Libraries Publishing 2024-02-01
Series:Journal of Transport and Land Use
Subjects:
Keywords: Traffic demand prediction, Similarity-based Principle, Spatio-temporal Graph Convolutional Neural Network model; activity-based geographic information; prediction of bicycle sharing ridership.
Online Access:https://www.jtlu.org/index.php/jtlu/article/view/2348
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