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    Kolmogorov–Arnold Networks for Accident Risk Prediction at Highway-Rail Grade Crossings

    Source: Journal of Transportation Engineering, Part A: Systems:;2026:;Volume ( 152 ):;issue: 008::page 04026049-1
    Author:
    Alabintei, Dengimowei D.
    ,
    Attoh-Okine, Nii
    DOI: 10.1061/JTEPBS.TEENG-9381
    Publisher: American Society of Civil Engineers
    Abstract: AbstractHighway-rail grade crossings, critical intersections where highways and railways meet, pose significant safety challenges, with approximately 2,000 incidents annually in the United States, according to the Federal Railroad Administration (FRA). ...Practical ApplicationsThis study demonstrates how crash history, traffic levels, highway features, and warning devices can be used together to estimate accident risk at highway-rail crossings. The results confirm that crossings with heavy traffic, higher ...
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      Kolmogorov–Arnold Networks for Accident Risk Prediction at Highway-Rail Grade Crossings

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4313717
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    • Journal of Transportation Engineering, Part A: Systems

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    contributor authorAlabintei, Dengimowei D.
    contributor authorAttoh-Okine, Nii
    date accessioned2026-08-20T20:56:58Z
    date available2026-08-20T20:56:58Z
    date copyright2026/05/24
    date issued2026
    identifier otherJTEPBS.TEENG-9381.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313717
    description abstractAbstractHighway-rail grade crossings, critical intersections where highways and railways meet, pose significant safety challenges, with approximately 2,000 incidents annually in the United States, according to the Federal Railroad Administration (FRA). ...Practical ApplicationsThis study demonstrates how crash history, traffic levels, highway features, and warning devices can be used together to estimate accident risk at highway-rail crossings. The results confirm that crossings with heavy traffic, higher ...
    publisherAmerican Society of Civil Engineers
    titleKolmogorov–Arnold Networks for Accident Risk Prediction at Highway-Rail Grade Crossings
    typeJournal Article
    journal volume152
    journal issue8
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/JTEPBS.TEENG-9381
    journal fristpage04026049-1
    journal lastpage04026049-12
    page12
    treeJournal of Transportation Engineering, Part A: Systems:;2026:;Volume ( 152 ):;issue: 008
    contenttypeFulltext
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