Self-Attention Graph Convolution Residual Network for Traffic Data Completion

Author:

Zhang Yong1ORCID,Wei Xiulan2ORCID,Zhang Xinyu1,Hu Yongli1ORCID,Yin Baocai1ORCID

Affiliation:

1. Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing Institute of Artificial Intelligence, Faculty of Information Technology, Beijing University of Technology, Beijing, China

2. Beijing Key Laboratory of Multimedia and Intelligent Software Technology, Beijing Institute of Artificial Intelligence, College of Metropolitan Transportation, Beijing University of Technology, Beijing, China

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Beijing Natural Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Information Systems and Management,Information Systems

Reference38 articles.

1. Tensor completion via a multi-linear low-n-rank factorization model

2. Deep bidirectional and unidirectional lstm recurrent neural network for network-wide traffic speed prediction;cui,2018

3. A tensor-based method for missing traffic data completion

4. Scalable low-rank autoregressive tensor learning for spatiotemporal traffic data imputation;chen,2020

5. Text-to-Traffic Generative Adversarial Network for Traffic Situation Generation

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