<?xml version="1.0" encoding="UTF-8"?>
<doi_batch version="5.3.1" xmlns="http://www.crossref.org/schema/5.3.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1" xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" xsi:schemaLocation="http://www.crossref.org/schema/5.3.1 http://www.crossref.org/schema/deposit/crossref5.3.1.xsd">
 <head>
  <doi_batch_id>aspg-24-1487-1791485084</doi_batch_id>
  <timestamp>20261008184444</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
  </depositor>
  <registrant>American Scientific Publishing Group</registrant>
 </head>
 <body>
  <journal>
   <journal_metadata language="en">
    <full_title>Journal of Neutrosophic and Fuzzy Systems</full_title>
    <abbrev_title>JNFS</abbrev_title>
    <issn media_type="print">2771-6430</issn>
    <issn media_type="electronic">2771-6449</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2023</year>
    </publication_date>
    <journal_volume>
     <volume>5</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Integrated Multi-Criteria Decision Making Via Trapezoidal Neutrosophic Sets to Evaluate the Risks of Failure Mode</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Mahmoud A.</given_name>
      <surname>Zaher</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Artificial Intelligence, Data Science department, Egyptian Russian University (ERU), Cairo, Egypt</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Nabil M.</given_name>
      <surname>Eldakhly</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Computers and Information, Sadat Academy for Management Sciences, Cairo, Egypt &amp; French University in Cairo, Egypt</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>The purpose of a failure mode and effect analysis (FMEA) is to improve the safety and dependability of a system, product, procedure, or facility by identifying potential points of failure and determining the consequences of such failures. The assessment of failure modes, the weighting of risk factors, and the ranking of failure modes are all areas where the conventional FMEA falls short when put to use in the real world. To assess the hazard of failure modes in a trapezoidal neutrosophic sets environment, this research proposes a model that combines the neutrosophic sets and MCDM technique such as WASPAS. The WASPAS MCDM method is used to calculate the weights of standards and order the alternatives. Advantages of trapezoidal neutrosophic numbers in dealing with uncertainty, ambiguity, and incompleteness are combined with the benefits of WASPAS to create the suggested risk prioritization strategy.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2023</year>
    </publication_date>
    <pages>
     <first_page>23</first_page>
     <last_page>29</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">1487</item_number>
    </publisher_item>
    <ai:program name="AccessIndicators">
     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/JNFS.050103</doi>
     <resource>https://www.americaspg.com/journal/24/article/1487</resource>
     <collection property="text-mining">
      <item>
       <resource mime_type="application/pdf">https://www.americaspg.com/storage/21674398366.pdf</resource>
      </item>
     </collection>
    </doi_data>
   </journal_article>
  </journal>
 </body>
</doi_batch>
