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    An Autoencoder-Based Machine- and Deep-Learning Approach for Predicting Bridge Deck Conditions in Texas

    Source: Journal of Structural Design and Construction Practice:;2025:;Volume ( 030 ):;issue: 004::page 04025080-1
    Author:
    Bayat, Mahmoud
    ,
    Kharel, Subham
    ,
    Li, Jianling
    DOI: 10.1061/JSDCCC.SCENG-1799
    Publisher: American Society of Civil Engineers
    Abstract: AbstractBridges are crucial to the global economy, facilitating mobility and accessibility. Effective monitoring and maintenance of these structures are vital due to aging, heavy traffic, and variable construction quality. While recent studies have ...Practical ApplicationsThe practical application of this research lies in its potential to enhance the accuracy and efficiency of predicting bridge deck condition ratings. Traditionally, condition ratings are assessed qualitatively by experts based on ...
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      An Autoencoder-Based Machine- and Deep-Learning Approach for Predicting Bridge Deck Conditions in Texas

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4313176
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    contributor authorBayat, Mahmoud
    contributor authorKharel, Subham
    contributor authorLi, Jianling
    date accessioned2026-08-20T12:10:04Z
    date available2026-08-20T12:10:04Z
    date copyright2025/07/01
    date issued2025
    identifier otherJSDCCC.SCENG-1799.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313176
    description abstractAbstractBridges are crucial to the global economy, facilitating mobility and accessibility. Effective monitoring and maintenance of these structures are vital due to aging, heavy traffic, and variable construction quality. While recent studies have ...Practical ApplicationsThe practical application of this research lies in its potential to enhance the accuracy and efficiency of predicting bridge deck condition ratings. Traditionally, condition ratings are assessed qualitatively by experts based on ...
    publisherAmerican Society of Civil Engineers
    titleAn Autoencoder-Based Machine- and Deep-Learning Approach for Predicting Bridge Deck Conditions in Texas
    typeJournal Article
    journal volume30
    journal issue4
    journal titleJournal of Structural Design and Construction Practice
    identifier doi10.1061/JSDCCC.SCENG-1799
    journal fristpage04025080-1
    journal lastpage04025080-16
    page16
    treeJournal of Structural Design and Construction Practice:;2025:;Volume ( 030 ):;issue: 004
    contenttypeFulltext
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