Multi-spatio-temporal Fusion Graph Recurrent Network for Traffic Forecasting

Wei Zhao; Shiqi Zhang; Bing Zhou; Bei Wang

doi:10.1016/j.engappai.2023.106615

ScienceGate Book Chapters

JOURNAL ARTICLE

Multi-spatio-temporal Fusion Graph Recurrent Network for Traffic Forecasting

Wei Zhao Shiqi Zhang Bing Zhou Bei Wang

Year: 2023 Journal: Engineering Applications of Artificial Intelligence Vol: 124 Pages: 106615-106615 Publisher: Elsevier BV

DOI: 10.1016/j.engappai.2023.106615

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Data mining Adjacency matrix Graph Sensor fusion Temporal database Adjacency list Artificial intelligence Theoretical computer science Algorithm

Metrics

Cited By

4.50

FWCI (Field Weighted Citation Impact)

Refs

0.92

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Traffic Prediction and Management Techniques

Physical Sciences → Engineering → Building and Construction

Transportation Planning and Optimization

Social Sciences → Social Sciences → Transportation

Human Mobility and Location-Based Analysis

Social Sciences → Social Sciences → Transportation

Multi-spatio-temporal Fusion Graph Recurrent Network for Traffic Forecasting

Metrics

Citation History

Topics

Related Documents

Decoupled multi-spatio-temporal fusion graph convolutional recurrent network for traffic prediction

Spatio-temporal multi-attention graph network for traffic forecasting

Spatio-temporal fusion graph convolutional network for traffic flow forecasting

Multi-graph spatio-temporal network for traffic accident risk forecasting

Spatio-Temporal Graph Network-Based Traffic Forecasting Method