Research on Traffic Congestion Forecast Based on Deep Learning
In recent years, the rapid economic development of China, the increase of the urban population, the continuous growth of private car ownership, the uneven distribution of traffic flow, and the local congestion of the road network have caused traffic congestion. Traffic congestion has become an inevi...
Main Authors: | Yangyang Qi, Zesheng Cheng |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-02-01
|
Series: | Information |
Subjects: | |
Online Access: | https://www.mdpi.com/2078-2489/14/2/108 |
Similar Items
-
A Deep Learning Framework About Traffic Flow Forecasting for Urban Traffic Emission Monitoring System
by: Baozhen Yao, et al.
Published: (2022-01-01) -
STAGCN: Spatial–Temporal Attention Graph Convolution Network for Traffic Forecasting
by: Yafeng Gu, et al.
Published: (2022-05-01) -
PMGCN: Progressive Multi-Graph Convolutional Network for Traffic Forecasting
by: Zhenxin Li, et al.
Published: (2023-06-01) -
Real-Time Traffic Data Analysis and Deep Learning-based Traffic Volume Classification for Congestion Mitigation at Urban Intersections
by: Omar Abdullah Hasan, et al.
Published: (2025-03-01) -
Graph Neural Network for Traffic Forecasting: The Research Progress
by: Weiwei Jiang, et al.
Published: (2023-02-01)