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

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    JSDCCC.SCENG-1799.pdf (2.091Mb)
    Date
    2025
    Author
    Bayat, Mahmoud
    Kharel, Subham
    Li, Jianling
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    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 ...
    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4313176
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