  <?xml version="1.0"?>
<journal>
 <journal_metadata>
  <full_title>International Journal of Neutrosophic Science</full_title>
  <abbrev_title>IJNS</abbrev_title>
  <issn media_type="print">2690-6805</issn>
  <issn media_type="electronic">2692-6148</issn>
  <doi_data>
   <doi>10.54216/IJNS</doi>
   <resource>https://www.americaspg.com/journals/show/3034</resource>
  </doi_data>
 </journal_metadata>
 <journal_issue>
  <publication_date media_type="print">
   <year>2020</year>
  </publication_date>
  <publication_date media_type="online">
   <year>2020</year>
  </publication_date>
 </journal_issue>
 <journal_article publication_type="full_text">
  <titles>
   <title>A Robust MCDM Framework for Cloud Service Selection Using Spherical Fermatean Neutrosophic Bonferroni Mean</title>
  </titles>
  <contributors>
   <organization sequence="first" contributor_role="author">Department of Mathematics, Sri GVG Visalakshi College for Women-642128, India</organization>
   <person_name sequence="first" contributor_role="author">
    <given_name>S.</given_name>
    <surname>S.</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of Mathematics, Sri GVG Visalakshi College for Women-642128, India</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>M.</given_name>
    <surname>Karpagadevi</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of Mathematics, Sri Krishna College of Engineering and Technology,-641008, India</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>S.</given_name>
    <surname>Krishnaprakash</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Laboratory of Information Processing, Faculty of Science Ben M’Sik, University Hassan II, Casablanca, India</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Said</given_name>
    <surname>Broumi</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of Mathematics, Dr. Mahalingam College of Engineering and Technology-642003, India</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>S.</given_name>
    <surname>Gomathi</surname>
   </person_name>
  </contributors>
  <jats:abstract xml:lang="en">
   <jats:p>This study presents an innovative approach to cloud service provider selection using the spherical Fermatean neutrosophic Bonferroni mean. As organizations increasingly rely on cloud services, selecting the optimal provider becomes critical, necessitating robust multi criteria decision making methods. Traditional approaches often fall short in capturing the diverse perspectives of decision-makers, leading to suboptimal choices. The spherical Fermatean neutrosophic Bonferroni mean addresses this gap by integrating a spherical representation that encompasses membership, non-membership and indeterminacy functions, enhanced by the Bonferroni mean. This structure effectively encapsulates the opinions of all decision makers, offering a comprehensive and balanced perspective. The study evaluates six cloud service providers based on four criteria: cost (nonbeneficiary), performance, security and scalability (beneficiary). Three decision makers with distinct priorities participate in the evaluation, ensuring a thorough assessment. The proposed spherical Fermatean neutrosophic Bonferroni mean method excels in resolving ambiguity and managing risk with greater precision than conventional FNSs, providing a more accurate and effective decision-making framework. A numerical example illustrates the practical application of spherical Fermatean neutrosophic Bonferroni mean, demonstrating its utility in selecting the optimal cloud service provider for an organization.</jats:p>
  </jats:abstract>
  <publication_date media_type="print">
   <year>2024</year>
  </publication_date>
  <publication_date media_type="online">
   <year>2024</year>
  </publication_date>
  <pages>
   <first_page>420</first_page>
   <last_page>431</last_page>
  </pages>
  <doi_data>
   <doi>10.54216/IJNS.240432</doi>
   <resource>https://www.americaspg.com/articleinfo/21/show/3034</resource>
  </doi_data>
 </journal_article>
</journal>
