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    Data-driven real-time prediction for attitude and position of super-large diameter shield using a hybrid deep learning approach

    New search for: Fu, Yanbin
    New search for: Chen, Lei
    New search for: Xiong, Hao
    New search for: Chen, Xiangsheng
    New search for: Lu, Andian
    New search for: Zeng, Yi
    New search for: Wang, Beiling

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    Data-driven real-time prediction for attitude and position of super-large diameter shield using a hybrid deep learning approach

    New search for: Fu, Yanbin
    New search for: Chen, Lei
    New search for: Xiong, Hao
    New search for: Chen, Xiangsheng
    New search for: Lu, Andian
    New search for: Zeng, Yi
    New search for: Wang, Beiling

    Access

    Download

    Data-driven real-time prediction for attitude and position of super-large diameter shield using a hybrid deep learning approach

    New search for: Fu, Yanbin
    New search for: Chen, Lei
    New search for: Xiong, Hao
    New search for: Chen, Xiangsheng
    New search for: Lu, Andian
    New search for: Zeng, Yi
    New search for: Wang, Beiling

    Access

    Download

    Access

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    Page navigation

    Document information
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    Document information
    Title:

    Data-driven real-time prediction for attitude and position of super-large diameter shield using a hybrid deep learning approach

    Additional title:

    Underground Space

    Contributors:

    Fu, Yanbin (author) / Chen, Lei (author) / Xiong, Hao (author) / Chen, Xiangsheng (author) / Lu, Andian (author) / Zeng, Yi (author) / Wang, Beiling (author)

    Published in:

    Underground Space ; 15 ; 275-297

    Publication date:

    2024-04-01

    ISSN:

    2467-9674

    DOI:

    https://doi.org/10.1016/j.undsp.2023.08.014

    Type of media:

    Article (Journal)

    Type of material:

    Electronic Resource

    Language:

    English

    Licence:

    http://creativecommons.org/licenses/by-nc-nd/4.0/

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