YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • ASCE
    • Journal of Materials in Civil Engineering
    • View Item
    •   YE&T Library
    • ASCE
    • Journal of Materials in Civil Engineering
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Predicting Aggregate Gradation Based on Pavement Surface Image Features Using Random Forest and Multilayer Perceptron Integrated Model

    Source: Journal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 004::page 04026050-1
    Author:
    Cao, Can
    ,
    Liu, Yancheng
    ,
    Jiao, Xiaolei
    ,
    Li, Yiming
    ,
    Xu, Yongli
    DOI: 10.1061/JMCEE7.MTENG-21647
    Publisher: American Society of Civil Engineers
    Abstract: AbstractAggregate gradation significantly impacts the road performance of asphalt pavement. However, current detection methods are often inefficient, destroying the pavement structure, and do not allow for quick real-time detection. The advancement of ...Practical ApplicationsIn the quality control of asphalt pavement construction, aggregate gradation detection represents a core mandatory inspection. However, traditional sieving tests are plagued by drawbacks such as lengthy cycles and the inability to ...
    • Download: (2.283Mb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Statistics

      Predicting Aggregate Gradation Based on Pavement Surface Image Features Using Random Forest and Multilayer Perceptron Integrated Model

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4312564
    Collections
    • Journal of Materials in Civil Engineering

    Show full item record

    contributor authorCao, Can
    contributor authorLiu, Yancheng
    contributor authorJiao, Xiaolei
    contributor authorLi, Yiming
    contributor authorXu, Yongli
    date accessioned2026-08-20T11:42:27Z
    date available2026-08-20T11:42:27Z
    date copyright2026/01/31
    date issued2026
    identifier otherJMCEE7.MTENG-21647.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312564
    description abstractAbstractAggregate gradation significantly impacts the road performance of asphalt pavement. However, current detection methods are often inefficient, destroying the pavement structure, and do not allow for quick real-time detection. The advancement of ...Practical ApplicationsIn the quality control of asphalt pavement construction, aggregate gradation detection represents a core mandatory inspection. However, traditional sieving tests are plagued by drawbacks such as lengthy cycles and the inability to ...
    publisherAmerican Society of Civil Engineers
    titlePredicting Aggregate Gradation Based on Pavement Surface Image Features Using Random Forest and Multilayer Perceptron Integrated Model
    typeJournal Article
    journal volume38
    journal issue4
    journal titleJournal of Materials in Civil Engineering
    identifier doi10.1061/JMCEE7.MTENG-21647
    journal fristpage04026050-1
    journal lastpage04026050-11
    page11
    treeJournal of Materials in Civil Engineering:;2026:;Volume ( 038 ):;issue: 004
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian