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...
Saved in:
| Main Authors: | Guifang Shi, Limei Luo |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2023/3448864 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Analysis of Passenger Flow Characteristics and Origin–Destination Passenger Flow Prediction in Urban Rail Transit Based on Deep Learning
by: Zhongwei Hou, et al.
Published: (2025-03-01) -
Impact Analysis of Large Shopping Malls on Inbound and Outbound Passenger Flow Rates at Urban Rail Transit Stations
by: ZHANG Xiaotian, et al.
Published: (2025-03-01) -
A Discrete-Event Simulation System for Estimating Passenger Flow in Urban Rail Transit
by: Suxiao CHEN, et al.
Published: (2025-03-01) -
Post-evaluation and Analysis of Passenger Flow on New Rail Transit Lines
by: LI Ke, et al.
Published: (2025-05-01) -
Forecasting Passenger Flow Distribution on Holidays for Urban Rail Transit Based on Destination Choice Behavior Analysis
by: Enjian Yao, et al.
Published: (2021-01-01)