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  <doi_batch_id>aspg-3-1108-1791417721</doi_batch_id>
  <timestamp>20261008000201</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
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  <journal>
   <journal_metadata language="en">
    <full_title>Fusion: Practice and Applications</full_title>
    <abbrev_title>FPA</abbrev_title>
    <issn media_type="print">2770-0070</issn>
    <issn media_type="electronic">2692-4048</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <journal_volume>
     <volume>7</volume>
    </journal_volume>
    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Integrated Decision Making Aided Model to Estimate the Risks of the Excavation System</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Lobna</given_name>
      <surname>Osman</surname>
      <affiliations>
       <institution>
        <institution_name>Delta Higher Institute for Engineering &amp; Technology, Department of Electronics and Communications Engineering, Egypt.</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>For the last years, a bibliometric examination of risk evaluation approaches for excavating systems has been presented in this publication. To develop an early warning system, it's essential to compile a list of possible dangers that can arise during excavation. Failure Mode and Effects Analysis (FMEA) is a useful approach. Traditional risk assessment techniques have been criticized for a variety of reasons, including a lack of correlation between risk variables, difficult arithmetic operations, and a lack of correctness and preciseness in the evaluations. A unique method of risk analysis in FMEA that uses digraphs and matrix approaches underneath the Pythagorean fuzzy scenario is presented in this research. To get started, we'll defy Pythagorean fuzzy numbers in a triangle form. Both language terminology and risk factor data and information are expressed using them (inclusive of occurrence, severity, and detection). The Pythagorean fuzzy digraph thus captures the interrelationships between the risk variables and the relative importance of each one, as seen in the figure. After that, we create a Pythagorean fuzzy test indicated for each identified failure mode and compute risk priority indexes to determine risk priorities. Using a metro station excavation as a case study, the accuracy of risk assessments in excavation is improved.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <pages>
     <first_page>110</first_page>
     <last_page>123</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">1108</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/FPA.070205</doi>
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