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    Machine-Learning Algorithms for Estimating Rutting Potential and Cracking Tolerance Index of Bituminous Mixtures

    Source: Journal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 001::page 04025484-1
    Author:
    Shaikh, Sadiya
    ,
    Gupta, Ankit
    ,
    Raj, Vishu
    ,
    Singh, Anshika
    DOI: 10.1061/JMCEE7.MTENG-21183
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThe present study aims to estimate Marshall-designed bituminous mixtures’ rutting and cracking resistance using different machine learning algorithms. The BS EN 12597-24 (dynamic creep test) and ASTM D8225-19 (Indirect Tensile Asphalt Cracking ...
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      Machine-Learning Algorithms for Estimating Rutting Potential and Cracking Tolerance Index of Bituminous Mixtures

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4312474
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    contributor authorShaikh, Sadiya
    contributor authorGupta, Ankit
    contributor authorRaj, Vishu
    contributor authorSingh, Anshika
    date accessioned2026-08-20T11:38:30Z
    date available2026-08-20T11:38:30Z
    date copyright2025/10/24
    date issued2026
    identifier otherJMCEE7.MTENG-21183.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312474
    description abstractAbstractThe present study aims to estimate Marshall-designed bituminous mixtures’ rutting and cracking resistance using different machine learning algorithms. The BS EN 12597-24 (dynamic creep test) and ASTM D8225-19 (Indirect Tensile Asphalt Cracking ...
    publisherAmerican Society of Civil Engineers
    titleMachine-Learning Algorithms for Estimating Rutting Potential and Cracking Tolerance Index of Bituminous Mixtures
    typeJournal Article
    journal volume38
    journal issue1
    journal titleJournal of Materials in Civil Engineering
    identifier doi10.1061/JMCEE7.MTENG-21183
    journal fristpage04025484-1
    journal lastpage04025484-16
    page16
    treeJournal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 001
    contenttypeFulltext
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