Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functions
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 gene...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-09-01
|
| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147719877613 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832547211493244928 |
|---|---|
| author | Muhammad Gulistan Mutaz Mohammad Faruk Karaaslan Seifedine Kadry Salma Khan Hafiz Abdul Wahab |
| author_facet | Muhammad Gulistan Mutaz Mohammad Faruk Karaaslan Seifedine Kadry Salma Khan Hafiz Abdul Wahab |
| author_sort | Muhammad Gulistan |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-3c90819d2cbe4ef286265f47bcd809d5 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2019-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-3c90819d2cbe4ef286265f47bcd809d52025-02-03T06:45:37ZengWileyInternational Journal of Distributed Sensor Networks1550-14772019-09-011510.1177/1550147719877613Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functionsMuhammad Gulistan0Mutaz Mohammad1Faruk Karaaslan2Seifedine Kadry3Salma Khan4Hafiz Abdul Wahab5Department of Mathematics and Statistics, Hazara University, Mansehra, PakistanDepartment of Mathematics, Zayed University, Abu Dhabi, United Arab EmiratesDepartment of Mathematics, Faculty of Sciences, Çankırı Karatekin University, Çankırı, TurkeyDepartment of Mathematics and Computer Science, Beirut Arab University, Beirut, LebanonDepartment of Mathematics and Statistics, Hazara University, Mansehra, PakistanDepartment of Mathematics and Statistics, Hazara University, Mansehra, PakistanThis 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.https://doi.org/10.1177/1550147719877613 |
| spellingShingle | Muhammad Gulistan Mutaz Mohammad Faruk Karaaslan Seifedine Kadry Salma Khan Hafiz Abdul Wahab Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functions International Journal of Distributed Sensor Networks |
| title | Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functions |
| title_full | Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functions |
| title_fullStr | Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functions |
| title_full_unstemmed | Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functions |
| title_short | Neutrosophic cubic Heronian mean operators with applications in multiple attribute group decision-making using cosine similarity functions |
| title_sort | neutrosophic cubic heronian mean operators with applications in multiple attribute group decision making using cosine similarity functions |
| url | https://doi.org/10.1177/1550147719877613 |
| work_keys_str_mv | AT muhammadgulistan neutrosophiccubicheronianmeanoperatorswithapplicationsinmultipleattributegroupdecisionmakingusingcosinesimilarityfunctions AT mutazmohammad neutrosophiccubicheronianmeanoperatorswithapplicationsinmultipleattributegroupdecisionmakingusingcosinesimilarityfunctions AT farukkaraaslan neutrosophiccubicheronianmeanoperatorswithapplicationsinmultipleattributegroupdecisionmakingusingcosinesimilarityfunctions AT seifedinekadry neutrosophiccubicheronianmeanoperatorswithapplicationsinmultipleattributegroupdecisionmakingusingcosinesimilarityfunctions AT salmakhan neutrosophiccubicheronianmeanoperatorswithapplicationsinmultipleattributegroupdecisionmakingusingcosinesimilarityfunctions AT hafizabdulwahab neutrosophiccubicheronianmeanoperatorswithapplicationsinmultipleattributegroupdecisionmakingusingcosinesimilarityfunctions |