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Laplacian integration of graph convolutional network with tensor completion for traffic prediction with missing data in inter-city highway network

Author

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  • Dong, Hanxuan
  • Ding, Fan
  • Tan, Huachun
  • Zhang, Hailong

Abstract

Traffic prediction on a large-scale road network is of great importance to various applications. However, many factors such as sensor failure and communication errors inevitably resulted in a sparse distribution of effective detection points with missing data, which resulting adversely affects the accuracy of traffic prediction.

Suggested Citation

  • Dong, Hanxuan & Ding, Fan & Tan, Huachun & Zhang, Hailong, 2022. "Laplacian integration of graph convolutional network with tensor completion for traffic prediction with missing data in inter-city highway network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    • Handle: RePEc:eee:phsmap:v:586:y:2022:i:c:s0378437121007470
    DOI: 10.1016/j.physa.2021.126474
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    References listed on IDEAS

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    1. Yang, Senyan & Wu, Jianping & Xu, Yanyan & Yang, Tao, 2019. "Revealing heterogeneous spatiotemporal traffic flow patterns of urban road network via tensor decomposition-based clustering approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    2. Chen, Xinqiang & Chen, Huixing & Yang, Yongsheng & Wu, Huafeng & Zhang, Wenhui & Zhao, Jiansen & Xiong, Yong, 2021. "Traffic flow prediction by an ensemble framework with data denoising and deep learning model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
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    Citations

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    Cited by:

    1. Zhang, Ke & Lin, Xi & Li, Meng, 2023. "Graph attention reinforcement learning with flexible matching policies for multi-depot vehicle routing problems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    2. Wenbao Zeng & Ketong Wang & Jianghua Zhou & Rongjun Cheng, 2023. "Traffic Flow Prediction Based on Hybrid Deep Learning Models Considering Missing Data and Multiple Factors," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    3. Ma, Changxi & Zhao, Mingxi, 2023. "Spatio-temporal multi-graph convolutional network based on wavelet analysis for vehicle speed prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).

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