Traffic Inflow and Outflow Forecasting by Modeling Intra- and Inter-Relationship Between Flows-Reference-Cited by-同舟云学术

Traffic Inflow and Outflow Forecasting by Modeling Intra- and Inter-Relationship Between Flows

Published:2022-11 Issue:11 Volume:23 Page:20202-20216
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Zhao Yiji¹^ORCID,Lin Youfang¹,Zhang Yongkai¹^ORCID,Wen Haomin¹^ORCID,Liu Yunxiao¹,Wu Hao²^ORCID,Wu Zhihao¹,Zhang Shuaichao³,Wan Huaiyu¹^ORCID

Affiliation:

1. Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China

2. School of Information Science and Engineering, Yunnan University, Yunnan, Kunming, China

3. Huawei Technologies Company Ltd., Shenzhen, China

Funder

Fundamental Research Funds for the Central Universities

Cooperation Project with Huawei Inc

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/9942712/09827999.pdf?arnumber=9827999

Reference48 articles.

1. Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks

2. Graph WaveNet for Deep Spatial-Temporal Graph Modeling

3. Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction

4. Deep Spatial–Temporal 3D Convolutional Neural Networks for Traffic Data Forecasting

5. Using LSTM and GRU neural network methods for traffic flow prediction

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