Improved Deep Hybrid Networks for Urban Traffic Flow Prediction Using Trajectory Data

Improved Deep Hybrid Networks for Urban Traffic Flow Prediction Using Trajectory Data

The urban traffic flow prediction is a significant issue in the intelligent transportation system. In consideration of nonlinear and spatial-temporal features of urban traffic data, we propose a deep hybrid neural network improved by greedy algorithm for urban traffic flow prediction with taxi GPS t...

Full description

Bibliographic Details
Main Authors: Zongtao Duan, Yun Yang, Kai Zhang, Yuanyuan Ni, Saurab Bajgain
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Deep hybrid networks
greedy policy
trajectory data
urban traffic-flow prediction
Online Access:https://ieeexplore.ieee.org/document/8377977/

Internet

https://ieeexplore.ieee.org/document/8377977/

Similar Items