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    Prediction of Compression Index Using Diverse Regression Models and Variable Combinations: Insight from a Large Geotechnical Information Database

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;2026:;Volume ( 152 ):;issue: 007::page 04026039-1
    Author:
    Yoo, Byeong-Soo
    ,
    Han, Jin-Tae
    ,
    Park, Hyun Il
    ,
    Yang, Eomzi
    DOI: 10.1061/JGGEFK.GTENG-13797
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThe compression index is a critical design parameter for estimating the consolidation behavior of clayey soils and planning construction schedules. However, its measurement typically requires more than a week for a single specimen. Therefore, to ...Practical ApplicationsReliable estimation of the compression index is essential for predicting settlement in clayey soils. Existing empirical equations often rely on limited data and subjective variable selection, reducing their applicability. This study ...
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      Prediction of Compression Index Using Diverse Regression Models and Variable Combinations: Insight from a Large Geotechnical Information Database

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4311478
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    • Journal of Geotechnical and Geoenvironmental Engineering

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    contributor authorYoo, Byeong-Soo
    contributor authorHan, Jin-Tae
    contributor authorPark, Hyun Il
    contributor authorYang, Eomzi
    date accessioned2026-08-20T10:56:42Z
    date available2026-08-20T10:56:42Z
    date copyright2026/05/05
    date issued2026
    identifier otherJGGEFK.GTENG-13797.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311478
    description abstractAbstractThe compression index is a critical design parameter for estimating the consolidation behavior of clayey soils and planning construction schedules. However, its measurement typically requires more than a week for a single specimen. Therefore, to ...Practical ApplicationsReliable estimation of the compression index is essential for predicting settlement in clayey soils. Existing empirical equations often rely on limited data and subjective variable selection, reducing their applicability. This study ...
    publisherAmerican Society of Civil Engineers
    titlePrediction of Compression Index Using Diverse Regression Models and Variable Combinations: Insight from a Large Geotechnical Information Database
    typeJournal Article
    journal volume152
    journal issue7
    journal titleJournal of Geotechnical and Geoenvironmental Engineering
    identifier doi10.1061/JGGEFK.GTENG-13797
    journal fristpage04026039-1
    journal lastpage04026039-14
    page14
    treeJournal of Geotechnical and Geoenvironmental Engineering:;2026:;Volume ( 152 ):;issue: 007
    contenttypeFulltext
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