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    A Multifidelity Neural Network Model for Predicting Deformation in Deep Excavations and Nearby Existing Tunnels

    Source: International Journal of Geomechanics:;2026:;Volume ( 026 ):;issue: 008::page 04026153-1
    Author:
    Liu, Mingpeng
    ,
    Lu, Dechun
    ,
    Shiau, Jim
    ,
    Lai, Fengwen
    ,
    Huang, Ming
    ,
    Zhou, Xin
    DOI: 10.1061/IJGNAI.GMENG-13743
    Publisher: American Society of Civil Engineers
    Abstract: Abstract Numerical modeling is an effective approach to investigating deformation responses caused by deep excavations; however, it often shows discrepancies when compared with field measurements. To this end, this study develops a multifidelity neural ...
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      A Multifidelity Neural Network Model for Predicting Deformation in Deep Excavations and Nearby Existing Tunnels

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314085
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    • International Journal of Geomechanics

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    contributor authorLiu, Mingpeng
    contributor authorLu, Dechun
    contributor authorShiau, Jim
    contributor authorLai, Fengwen
    contributor authorHuang, Ming
    contributor authorZhou, Xin
    date accessioned2026-08-20T21:11:21Z
    date available2026-08-20T21:11:21Z
    date copyright2026/06/05
    date issued2026
    identifier otherIJGNAI.GMENG-13743.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314085
    description abstractAbstract Numerical modeling is an effective approach to investigating deformation responses caused by deep excavations; however, it often shows discrepancies when compared with field measurements. To this end, this study develops a multifidelity neural ...
    publisherAmerican Society of Civil Engineers
    titleA Multifidelity Neural Network Model for Predicting Deformation in Deep Excavations and Nearby Existing Tunnels
    typeJournal Article
    journal volume26
    journal issue8
    journal titleInternational Journal of Geomechanics
    identifier doi10.1061/IJGNAI.GMENG-13743
    journal fristpage04026153-1
    journal lastpage04026153-16
    page16
    treeInternational Journal of Geomechanics:;2026:;Volume ( 026 ):;issue: 008
    contenttypeFulltext
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