SST-GNN: simplified spatio-temporal traffic forecasting model using graph neural network

Keywords

• graph neural networks
• positional encoding
• traffic prediction
• temporal dependencies
• periodic traffic patterns
• PEMS
• long-range dependencies
• street intersections
• spatial dependence

CCDS Authors

Amit Roy

Amit Roy

• Research Assistant, CCDS

PhD Student

Purdue University

Published at

PAKDD, IJCNN

Research Interests

Machine Learning

Kashob Kumar Roy

Kashob Kumar Roy

• Research Assistant, CCDS

PhD Student

University of Illinois Urbana-Champaign

Published at

PAKDD, IJCNN

Research Interests

Machine Learning

Amin Ahsan Ali, PhD

Amin Ahsan Ali, PhD

• Director, AI/ML Wing

Professor

Department of Computer Science and Engineering

Independent University, Bangladesh

Published at

ACL, CHI, UbiComp, ECCV, IJCAI, ECAI, WACV, IPSN, PAKDD, LREC, IJCNN, ICPR, ICIP, BEA, BLP, ICMLA, Scientific Reports, Scientific Data, Pattern Recognition, Information Sciences, Ad Hoc Networks, Drug and Alcohol Dependence, PLOS ONE

Research Interests

Artificial Intelligence, Machine Learning

Prof. M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

• Founder Director, CCDS
• Director, AI/ML, HCI & DS Wings

Professor

+1 more affiliation

Department of Information Sciences and Technology

George Mason University, USA

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

AKM Mahbubur Rahman, PhD

AKM Mahbubur Rahman, PhD

• Director, DS & IPT Wings

Associate Professor

Department of Computer Science and Engineering

Independent University, Bangladesh

Published at

CHI, ECCV, WACV, PAKDD, LREC, IJCNN, ICPR, ICIP, HCII, BEA, Scientific Reports, Information Sciences

References

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7. 7.Rongzhou Huang, Chuyin Huang, Yubao Liu, Genan Dai, Weiyang Kong. (2020). LSGCN: Long Short-Term Traffic Prediction with Graph Convolutional Networks. , 2355–2361[10.24963/ijcai.2020/326]
8. 8.Cen Chen, Kenli Li, Sin G. Teo, Xiaofeng Zou, Kang Wang, Jie Wang, Zeng Zeng. (2019). Gated Residual Recurrent Graph Neural Networks for Traffic Prediction. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 485–492[10.1609/aaai.v33i01.3301485]
9. 9.Shen Fang, Qi Zhang, Gaofeng Meng, Shiming Xiang, Chunhong Pan. (2019). GSTNet: Global Spatial-Temporal Network for Traffic Flow Prediction. , 2286–2293[10.24963/ijcai.2019/317]
10. 10.Cheonbok Park, Chunggi Lee, Hyojin Bahng, Yunwon Tae, Seungmin Jin, Ki-Hwan Kim, Sungahn Ko, Jaegul Choo. (2020). ST-GRAT: A Novel Spatio-temporal Graph Attention Networks for Accurately Forecasting Dynamically Changing Road Speed. , 1215–1224[10.1145/3340531.3411940]
11. 11.William L. Hamilton, Rex Ying, Jure Leskovec. (2017). Inductive Representation Learning on Large Graphs. arXiv (Cornell University), 30, 1024–1034[10.48550/arxiv.1706.02216]
12. 12.Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu. (2017). Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic\n Forecasting. arXiv (Cornell University)[10.48550/arxiv.1707.01926]
13. 13.Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra. (2020). Beyond Homophily in Graph Neural Networks: Current Limitations and\n Effective Designs. arXiv (Cornell University)[10.48550/arxiv.2006.11468]

Cited By

1. 1.Lei Chang, Wenxi Yang, Kaiyuan Qi, Tao Cui, Lianfei Yu, Zhijian Qu, Chongguang Ren. (2024). Multiscale Spatio-Temporal Aware Graph Recurrent Neural Network for Traffic Prediction. Research Square[10.21203/rs.3.rs-5257185/v1]