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Dynamic traveling time forecasting based on spatial-temporal graph convolutional networks

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (NSFC) (Grant No. 62002216), the Shanghai Sailing Program (No. 20YF1414400), the Collaborative Innovation Platform of Electronic Information Master of Shanghai Polytechnic University (SSPU) (No. A10GY21F015), the Research Projects of Shanghai Polytechnic University (Nos. EGD22QD03, EGD23DS05), the Key Disciplines of Computer Science and Technology of SSPU and the Construction of Electronic Information Master Degree of SSPU.

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Authors and Affiliations

  1. School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, 201209, China

    Fangshu Chen, Yufei Zhang, Xiankai Meng, Yanqiang Qi & Jiahui Wang

  2. College of Computer Science, Zhejiang University, Hangzhou, 310027, China

    Lu Chen

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  1. Fangshu Chen
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  2. Yufei Zhang
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  3. Lu Chen
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  4. Xiankai Meng
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  5. Yanqiang Qi
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  6. Jiahui Wang
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Corresponding author

Correspondence to Jiahui Wang.

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Competing interests The authors declare that they have no competing interests or financial conflicts to disclose.

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Supporting information The supporting information is available online at journal.hep.com.cn and link.springer.com.

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Chen, F., Zhang, Y., Chen, L. et al. Dynamic traveling time forecasting based on spatial-temporal graph convolutional networks. Front. Comput. Sci. 17, 176615 (2023). https://doi.org/10.1007/s11704-023-2704-x

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