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Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functions

  • Muhammad Gulistan
  • , Mutaz Mohammad
  • , Faruk Karaaslan
  • , Seifedine Kadry
  • , Salma Khan
  • , Hafiz Abdul Wahab
  • Hazara University
  • Zayed University
  • Çankiri Karatekin University
  • Beirut Arab University

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

This article introduces the concept of Heronian mean operators, geometric Heronian mean operators, neutrosophic cubic number–improved generalized weighted Heronian mean operators, neutrosophic cubic number–improved generalized weighted geometric Heronian mean operators. These operators actually generalize the operators of fuzzy sets, cubic sets, and neutrosophic sets. We investigate the average weighted operator on neutrosophic cubic sets and weighted geometric operator on neutrosophic cubic sets to aggregate the neutrosophic cubic information. After this, based on average weighted and geometric weighted and cosine similarity function in neutrosophic cubic sets, we developed a multiple attribute group decision-making method. Finally, we give a mathematical example to illustrate the usefulness and application of the proposed method.

Original languageEnglish
JournalInternational Journal of Distributed Sensor Networks
Volume15
Issue number9
DOIs
StatePublished - Sep 2019
Externally publishedYes

Keywords

  • Heronian mean operator
  • Neutrosophic set
  • geometric Heronian mean operator
  • multiple attribute decision-making problem
  • neutrosophic cubic set

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