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    Use of the Relevance Vector Machine for Prediction of an Overconsolidation Ratio

    Source: International Journal of Geomechanics:;2013:;Volume ( 013 ):;issue: 001
    Author:
    Pijush
    ,
    Samui
    ,
    Pradeep
    ,
    Kurup
    DOI: 10.1061/(ASCE)GM.1943-5622.0000172
    Publisher: American Society of Civil Engineers
    Abstract: This article uses the relevance vector machine (RVM) for the prediction of the overconsolidation ratio (OCR) of fine-grained soils based on piezocone penetration test data. RVM provides an empirical Bayes method of function approximation by kernel basis expansion. It uses the corrected cone resistance (
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      Use of the Relevance Vector Machine for Prediction of an Overconsolidation Ratio

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/61572
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    • International Journal of Geomechanics

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    contributor authorPijush
    contributor authorSamui
    contributor authorPradeep
    contributor authorKurup
    date accessioned2017-05-08T21:45:26Z
    date available2017-05-08T21:45:26Z
    date copyrightFebruary 2013
    date issued2013
    identifier other%28asce%29gm%2E1943-5622%2E0000185.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/61572
    description abstractThis article uses the relevance vector machine (RVM) for the prediction of the overconsolidation ratio (OCR) of fine-grained soils based on piezocone penetration test data. RVM provides an empirical Bayes method of function approximation by kernel basis expansion. It uses the corrected cone resistance (
    publisherAmerican Society of Civil Engineers
    titleUse of the Relevance Vector Machine for Prediction of an Overconsolidation Ratio
    typeJournal Paper
    journal volume13
    journal issue1
    journal titleInternational Journal of Geomechanics
    identifier doi10.1061/(ASCE)GM.1943-5622.0000172
    treeInternational Journal of Geomechanics:;2013:;Volume ( 013 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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