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    Bayesian Back Analysis of Spatial Variability with Machine Learning Surrogates 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2025:;Volume ( 011 ):;issue: 002:;page 04025006-1
    Author(s): Xiaoying Chen; Shen Wang; Hao-Qing Yang; Lulu Zhang; Chao-Sheng Tang
    Publisher: American Society of Civil Engineers
    Abstract: Geotechnical sensors provide the advantage of directly monitoring model responses that accurately reflect field conditions. Within these field monitoring data lies the latent potential to glean insights into soil parameters. ...
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian