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  <doi_batch_id>aspg-21-1265-1791475500</doi_batch_id>
  <timestamp>20261008160500</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
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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>2022</year>
    </publication_date>
    <journal_volume>
     <volume>19</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Agriculture Production Decision Making using Generalized q-Rung Neutrosophic Soft Set Method</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>G.</given_name>
      <surname>Shanmugam</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Advanced Mathematical Science, Saveetha School of Engineering, Saveetha University, Saveetha Institute of Medical and Technical Sciences, Chennai-602105, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>M.</given_name>
      <surname>Palanikumar</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Advanced Mathematical Science, Saveetha School of Engineering, Saveetha University, Saveetha Institute of Medical and Technical Sciences, Chennai-602105, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>K.</given_name>
      <surname>Arulmozhi</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Mathematics, Bharath Institute of Higher Education and Research, Tamil Nadu, Chennai-600073, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Aiyared</given_name>
      <surname>Iampan</surname>
      <affiliations>
       <institution>
        <institution_name>Fuzzy Algebras and Decision-Making Problems Research Unit, Department of Mathematics, School of Science, University of Phayao, Mae Ka, Mueang, Phayao 56000, Thailand</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Said</given_name>
      <surname>Broumi</surname>
      <affiliations>
       <institution>
        <institution_name>Laboratory of Information Processing, Faculty of Science Ben M’Sik, Universit´s Hassan II, BP 7955 Casablanca, Morocco</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>This paper introduces the generalized q-rung neutrosophic soft set (GqRNSSS) theory and its use to solve actual</jats:p>
     <jats:p>problems. We also define a few operations that make use of the GqRNSSS. The GqRNSSS is constructed</jats:p>
     <jats:p>by generalizing both the Pythagorean neutrosophic soft set (PyNSSS) and Pythagorean fuzzy soft set (PyFSS).</jats:p>
     <jats:p>We give a method for agricultural output that is based on the proposed similarity measure of GqRNSSS. If two</jats:p>
     <jats:p>GqRNSSS are compared, it can be determined whether or not a person produces good agricultural output. We</jats:p>
     <jats:p>support a strategy for dealing with the decision-making (DM) problem that makes use of the generalized qrung</jats:p>
     <jats:p>soft set model. In this article, we discuss the application of a similarity measure between two GqRNSSS</jats:p>
     <jats:p>in agricultural output. Show how they can be successfully applied to challenges with uncertainty.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2022</year>
    </publication_date>
    <pages>
     <first_page>166</first_page>
     <last_page>176</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">1265</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>10.54216/IJNS.190112</doi>
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