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    k-Nearest Neighbor Model for Multiple-Time-Step Prediction of Short-Term Traffic Condition

    Source: Journal of Transportation Engineering, Part A: Systems:;2016:;Volume ( 142 ):;issue: 006
    Author:
    Bin Yu
    ,
    Xiaolin Song
    ,
    Feng Guan
    ,
    Zhiming Yang
    ,
    Baozhen Yao
    DOI: 10.1061/(ASCE)TE.1943-5436.0000816
    Publisher: American Society of Civil Engineers
    Abstract: One of the most critical functions of an intelligent transportation system (ITS) is to provide accurate and real-time prediction of traffic condition. This paper develops a short-term traffic condition prediction model based on the
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      k-Nearest Neighbor Model for Multiple-Time-Step Prediction of Short-Term Traffic Condition

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    http://yetl.yabesh.ir/yetl1/handle/yetl/82954
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    contributor authorBin Yu
    contributor authorXiaolin Song
    contributor authorFeng Guan
    contributor authorZhiming Yang
    contributor authorBaozhen Yao
    date accessioned2017-05-08T22:34:38Z
    date available2017-05-08T22:34:38Z
    date copyrightJune 2016
    date issued2016
    identifier other50106815.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/82954
    description abstractOne of the most critical functions of an intelligent transportation system (ITS) is to provide accurate and real-time prediction of traffic condition. This paper develops a short-term traffic condition prediction model based on the
    publisherAmerican Society of Civil Engineers
    titlek-Nearest Neighbor Model for Multiple-Time-Step Prediction of Short-Term Traffic Condition
    typeJournal Paper
    journal volume142
    journal issue6
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/(ASCE)TE.1943-5436.0000816
    treeJournal of Transportation Engineering, Part A: Systems:;2016:;Volume ( 142 ):;issue: 006
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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