YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • ASCE
    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
    • View Item
    •   YE&T Library
    • ASCE
    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: 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

    An Improved Dempster–Shafer Evidence Theory Based on the Chebyshev Distance and Its Application in Rock Burst Prewarnings

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2024:;Volume ( 010 ):;issue: 001::page 04023055-1
    Author:
    Faxing Zhang
    ,
    Liming Zhang
    ,
    Zhongyuan Liu
    ,
    Fanzhen Meng
    ,
    Xiaoshan Wang
    ,
    Jinhao Wen
    ,
    Liyan Gao
    DOI: 10.1061/AJRUA6.RUENG-1201
    Publisher: ASCE
    Abstract: The prewarning and responses of different monitoring indices are out of sync in engineering disaster warning, and the disaster risk assessment is inaccurate based on individual response index or comparison with different indices. The traditional Dempster–Shafer (DS) evidence theory cannot readily integrate the conflicting multivariate monitoring data. In the present study, the DS evidence theory was improved by integrating various conflicting multivariate monitoring data, and the application condition, advantages, and disadvantages of those modified methods based on the DS evidence theory were investigated. An improved DS evidence theory method was proposed based on the Chebyshev distance and the zero-divisor modified evidence source method. The results indicated that the improved DS evidence theory based on the Chebyshev distance performs well in both integrating the conflicting and nonconflicting monitoring data and is superior to other improved methods in suppressing interfering evidence with good stability. The proposed improved DS evidence theory based on the Chebyshev distance is then applied to rock burst prewarning, and the prewarning model is established based on multiphysics in situ monitoring data. The probability with various risk levels is employed to assess the safety state, which can reflect the degree of rock burst. The risk of rock burst can be quantitatively predicted using this proposed method, which can provide some guidance in the prewarning of engineering disasters.
    • Download: (2.192Mb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      An Improved Dempster–Shafer Evidence Theory Based on the Chebyshev Distance and Its Application in Rock Burst Prewarnings

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4297389
    Collections
    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

    Show full item record

    contributor authorFaxing Zhang
    contributor authorLiming Zhang
    contributor authorZhongyuan Liu
    contributor authorFanzhen Meng
    contributor authorXiaoshan Wang
    contributor authorJinhao Wen
    contributor authorLiyan Gao
    date accessioned2024-04-27T22:44:36Z
    date available2024-04-27T22:44:36Z
    date issued2024/03/01
    identifier other10.1061-AJRUA6.RUENG-1201.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4297389
    description abstractThe prewarning and responses of different monitoring indices are out of sync in engineering disaster warning, and the disaster risk assessment is inaccurate based on individual response index or comparison with different indices. The traditional Dempster–Shafer (DS) evidence theory cannot readily integrate the conflicting multivariate monitoring data. In the present study, the DS evidence theory was improved by integrating various conflicting multivariate monitoring data, and the application condition, advantages, and disadvantages of those modified methods based on the DS evidence theory were investigated. An improved DS evidence theory method was proposed based on the Chebyshev distance and the zero-divisor modified evidence source method. The results indicated that the improved DS evidence theory based on the Chebyshev distance performs well in both integrating the conflicting and nonconflicting monitoring data and is superior to other improved methods in suppressing interfering evidence with good stability. The proposed improved DS evidence theory based on the Chebyshev distance is then applied to rock burst prewarning, and the prewarning model is established based on multiphysics in situ monitoring data. The probability with various risk levels is employed to assess the safety state, which can reflect the degree of rock burst. The risk of rock burst can be quantitatively predicted using this proposed method, which can provide some guidance in the prewarning of engineering disasters.
    publisherASCE
    titleAn Improved Dempster–Shafer Evidence Theory Based on the Chebyshev Distance and Its Application in Rock Burst Prewarnings
    typeJournal Article
    journal volume10
    journal issue1
    journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
    identifier doi10.1061/AJRUA6.RUENG-1201
    journal fristpage04023055-1
    journal lastpage04023055-12
    page12
    treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2024:;Volume ( 010 ):;issue: 001
    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