Prediction and Impact Analysis of Passenger Flow in Urban Rail Transit in the Postpandemic Era
In the postpandemic era, exploring the relationship between the daily new COVID-19 cases and passenger flow in urban rail transit can help effectively predict the impact of future pandemic situations on rail transit. In this study, based on a gated recurrent unit (GRU) neural network model, the dail...
Main Authors: | Guifang Shi, Limei Luo |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2023-01-01
|
Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2023/3448864 |
Similar Items
-
Short-time Prediction of Urban Rail Transit Passenger Flow
by: Jing Xuan, et al.
Published: (2024-01-01) -
Integrated Prediction Model for Urban Rail Transit Station Feeder Passenger Flow
by: Junchen DAI, et al.
Published: (2024-02-01) -
Prevention of allergies in the postpandemic era
by: Gary Wong
Published: (2023-12-01) -
Passenger Flow Scale Prediction of Urban Rail Transit Stations Based on Multilayer Perceptron (MLP)
by: Luzhou Lin, et al.
Published: (2023-01-01) -
Analysis of the Impacts of Passenger Demand on the Profitability of Different Types of Urban Rail Transit
by: Qi Zhou, et al.
Published: (2023-02-01)