Research on Traffic Flow Forecasting Method Based on Graph Neural Network-Reference-Cited by-同舟云学术

Research on Traffic Flow Forecasting Method Based on Graph Neural Network

Published:2022-06-10 Issue: Volume: Page:
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Container-title:2022 IEEE 2nd International Conference on Software Engineering and Artificial Intelligence (SEAI)
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Author:

Wenjuan Xiao¹,Jianfeng Liu²

Affiliation:

1. College of Electrical Engineering, Northwest MinZu University,Lanzhou,China

2. Traffic Research Institute, Lanzhou Traffic Police Detachment,Lanzhou,China

Funder

Fundamental Research Funds for the Central Universities

Northwest MinZu University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9832024/9832026/09832353.pdf?arnumber=9832353

Reference6 articles.

1. Convolutional neural networks on graphs with fast localized spectral filtering;defferrard;Proceedings of the 30th International Conference on Neural Information Processing Systems,2016

2. A Comprehensive Survey on Graph Neural Networks

3. Graph Attention Networks[C];vcli?kovi?;International Conference on Learning Representations (ICLR),2018

4. Semi-Supervised Classification with Graph Convolutional Networks[C];kipf;International Conference on Learning Representations (ICLR),2016

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3. Graph Neural Networks for Traffic Pattern Recognition: An Overview;2023 IEEE International Conference on Smart Mobility (SM);2023-03-19

4. Spatial-Temporal Dynamic Graph Convolutional Neural Network for Traffic Prediction;IEEE Access;2023

5. Traffic Flow Prediction Base on Feature Fusion of Multi-modal Data;2022 IEEE 8th International Conference on Computer and Communications (ICCC);2022-12-09