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    Slope Reliability Analysis Using a Convolutional Neural Networks Surrogate Model with Emphasis on the Nonstationary Spatial Variability of Soil Properties

    Source: International Journal of Geomechanics:;2026:;Volume ( 026 ):;issue: 002::page 04025338-1
    Author:
    Zhang, Sheng
    ,
    Ding, Li
    ,
    Yang, Rui
    ,
    Zhang, Feng
    ,
    Tong, Chen-Xi
    DOI: 10.1061/IJGNAI.GMENG-11760
    Publisher: American Society of Civil Engineers
    Abstract: Abstract Slope reliability analysis has always been a research focus for geotechnical engineers. Currently, most studies use stationary random fields to simulate the spatial variability of soil parameters. However, many field test data show that soil ...
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      Slope Reliability Analysis Using a Convolutional Neural Networks Surrogate Model with Emphasis on the Nonstationary Spatial Variability of Soil Properties

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4312937
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    • International Journal of Geomechanics

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    contributor authorZhang, Sheng
    contributor authorDing, Li
    contributor authorYang, Rui
    contributor authorZhang, Feng
    contributor authorTong, Chen-Xi
    date accessioned2026-08-20T11:59:14Z
    date available2026-08-20T11:59:14Z
    date copyright2025/11/26
    date issued2026
    identifier otherIJGNAI.GMENG-11760.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312937
    description abstractAbstract Slope reliability analysis has always been a research focus for geotechnical engineers. Currently, most studies use stationary random fields to simulate the spatial variability of soil parameters. However, many field test data show that soil ...
    publisherAmerican Society of Civil Engineers
    titleSlope Reliability Analysis Using a Convolutional Neural Networks Surrogate Model with Emphasis on the Nonstationary Spatial Variability of Soil Properties
    typeJournal Article
    journal volume26
    journal issue2
    journal titleInternational Journal of Geomechanics
    identifier doi10.1061/IJGNAI.GMENG-11760
    journal fristpage04025338-1
    journal lastpage04025338-14
    page14
    treeInternational Journal of Geomechanics:;2026:;Volume ( 026 ):;issue: 002
    contenttypeFulltext
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