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    Genetic Feature Selection and Multistage Deep Learning for Bridge Substructure Condition Prediction

    Source: Journal of Performance of Constructed Facilities:;2026:;Volume ( 040 ):;issue: 004::page 04026018-1
    Author:
    Awuku, Bright
    ,
    Asa, Eric
    DOI: 10.1061/JPCFEV.CFENG-5198
    Publisher: American Society of Civil Engineers
    Abstract: AbstractTransportation agencies rely on accurate predictions of bridge substructure conditions for planning, resource allocation, and ensuring the safety of their infrastructure. Traditional deterioration models fail to adequately capture the complex ...
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      Genetic Feature Selection and Multistage Deep Learning for Bridge Substructure Condition Prediction

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4312944
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    contributor authorAwuku, Bright
    contributor authorAsa, Eric
    date accessioned2026-08-20T11:59:31Z
    date available2026-08-20T11:59:31Z
    date copyright2026/04/27
    date issued2026
    identifier otherJPCFEV.CFENG-5198.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312944
    description abstractAbstractTransportation agencies rely on accurate predictions of bridge substructure conditions for planning, resource allocation, and ensuring the safety of their infrastructure. Traditional deterioration models fail to adequately capture the complex ...
    publisherAmerican Society of Civil Engineers
    titleGenetic Feature Selection and Multistage Deep Learning for Bridge Substructure Condition Prediction
    typeJournal Article
    journal volume40
    journal issue4
    journal titleJournal of Performance of Constructed Facilities
    identifier doi10.1061/JPCFEV.CFENG-5198
    journal fristpage04026018-1
    journal lastpage04026018-18
    page18
    treeJournal of Performance of Constructed Facilities:;2026:;Volume ( 040 ):;issue: 004
    contenttypeFulltext
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