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  <doi_batch_id>aspg-21-2761-1791468715</doi_batch_id>
  <timestamp>20261008141155</timestamp>
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   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
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  <journal>
   <journal_metadata language="en">
    <full_title>International Journal of Neutrosophic Science</full_title>
    <abbrev_title>IJNS</abbrev_title>
    <issn media_type="print">2692-6148</issn>
    <issn media_type="electronic">2690-6805</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <journal_volume>
     <volume>24</volume>
    </journal_volume>
    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>On the Development of Fuzzy Estimators for Life Time Distributions based on Censored Fuzzy Life Times</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Mohammad</given_name>
      <surname>Abiad</surname>
      <affiliations>
       <institution>
        <institution_name>College of Business Administration, American University of the Middle East, Kuwait</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Muhammad</given_name>
      <surname>Shafiq</surname>
      <affiliations>
       <institution>
        <institution_name>Institute of Numerical Sciences, Kohat University of Science &amp; Technology, KP, Pakistan</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Syed Habib</given_name>
      <surname>Shah</surname>
      <affiliations>
       <institution>
        <institution_name>Institute of Numerical Sciences, Kohat University of Science &amp; Technology, KP, Pakistan</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Muhammad</given_name>
      <surname>Atif</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Statistics, University of Peshawar, KP, Pakistan</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Lifetime analyses comprise the techniques dealing with observations obtained from the occurrence of a specified event(s). In most of the situations dealing with lifetime observations, some units are recorded as censored observations. Dealing with censored observations makes these techniques unique. Countless standard statistical tools are available for inference based on censored lifetime observations. These classical techniques consider lifetime observations as precise numbers and ignore the uncertainty of single observations. Whereas in practical applications it is not possible to measure life times as precise numbers, they are always more or less nonprecise. The imprecision in measurements can be covered by neutrosophic set. Fuzzy estimators for life time distributions potentially use neutrosophic system to model and analyze the inherent uncertainties and neutalities present in the data and the parameter estimates. This study aimed to obtain estimators for the Weibull parameters and two exponential parameters based on the up-to-date fuzzy number approach, a special case for neutrosophic set. The suggested estimators incorporate fuzziness in addition to random variation, which makes these estimators more realistic. The same techniques need to be extended to fuzzy and neutrosophic sets.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <pages>
     <first_page>198</first_page>
     <last_page>209</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">2761</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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    <doi_data>
     <doi>10.54216/IJNS.240217</doi>
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