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Urban road network short-term traffic flow prediction model based on associated road chain group
更新时间：2025-05-26

    • Urban road network short-term traffic flow prediction model based on associated road chain group

    • “In the field of urban traffic flow prediction, researchers have proposed a traffic flow prediction model based on density peak clustering algorithm and long short-term memory neural network. The application of the model in Beijing's road network shows an accuracy of over 95%.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 53, Issue 11, Pages: 3104-3112(2023)
    • 作者机构：

      1.北京工业大学 交通工程北京市重点实验室， 北京 100124

      2.福建省高速公路联网运营有限公司， 福州 350019

      3.北京百度智行科技有限公司 智能交通业务拓展部， 北京 100085

      4.北京市交通委员会， 北京 100161

      5.北京市交通运行监测调度中心， 北京 100161

      6.综合交通运行监测与服务北京市重点实验室， 北京 100161

    • DOI：10.13229/j.cnki.jdxbgxb.20211391    

      CLC： U491.14

    • Received：16 December 2021，

      Published：01 November 2023

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  • WENG Jian-cheng,WEI Rui-cong,HE Han-mei,et al.Urban road network short-term traffic flow prediction model based on associated road chain group[J].Journal of Jilin University(Engineering and Technology Edition),2023,53(11):3104-3112. DOI： 10.13229/j.cnki.jdxbgxb.20211391.

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