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Traffic accident anticipation baed on spatial-temporal relational learning and convolutional gated recurrent network
更新时间：2025-05-26

    • Traffic accident anticipation baed on spatial-temporal relational learning and convolutional gated recurrent network

    • “In the field of traffic accident risk prediction, researchers have proposed a model GST that combines ViT, GRU, and MLP Mixer to effectively predict accident probability and provide early warning, providing assistance for road safety driving.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 55, Issue 3, Pages: 954-962(2025)
    • 作者机构：

      1.长春理工大学 物理学院， 长春 130012

      2.温州理工学院 建筑与能源工程学院，浙江 温州 325035

    • DOI：10.13229/j.cnki.jdxbgxb.20231228    

      CLC： TP301.6

    • Received：09 November 2023，

      Published：01 March 2025

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  • JIANG Sheng,WANG Yi-di,XIE Rui-lin,et al.Traffic accident anticipation baed on spatial-temporal relational learning and convolutional gated recurrent network[J].Journal of Jilin University(Engineering and Technology Edition),2025,55(03):954-962. DOI： 10.13229/j.cnki.jdxbgxb.20231228.

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