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

Hanxuan Dong, Fan Ding, Huachun Tan and Hailong Zhang

Physica A: Statistical Mechanics and its Applications, 2022, vol. 586, issue C

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.

Keywords: Traffic prediction; Graph convolutional network; Missing data; Tensor completion; Graph Laplace (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:586:y:2022:i:c:s0378437121007470

DOI: 10.1016/j.physa.2021.126474

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