Evaluation of the product quality of the online shopping platform using t-spherical fuzzy preference relations
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Choonkil | - |
dc.contributor.author | Ashraf, Shahzaib | - |
dc.contributor.author | Rehman, Noor | - |
dc.contributor.author | Abdullah, Saleem | - |
dc.contributor.author | Aslam, Muhammad | - |
dc.date.accessioned | 2022-07-06T02:22:17Z | - |
dc.date.available | 2022-07-06T02:22:17Z | - |
dc.date.created | 2022-01-05 | - |
dc.date.issued | 2021-12 | - |
dc.identifier.issn | 1064-1246 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/138594 | - |
dc.description.abstract | As a generalization of Pythagorean fuzzy sets and picture fuzzy sets, spherical fuzzy sets provide decision makers more flexible space in expressing their opinions. Preference relations have received widespread acceptance as an efficient tool in representing decision makers' preference over alternatives in the decision-making process. In this paper, some new preference relations are investigated based on the spherical fuzzy sets. Firstly, the deficiency of the existing operating laws is elaborated in detail and three cases are described to identify the accuracy of the proposed operating laws in the context of t-spherical fuzzy environment. Also, a novel score function is proposed to obtain the consistent value in ranking of the alternatives. The backbone of this research, t-spherical fuzzy preference relation, consistent t-spherical fuzzy preference relations, incomplete t-spherical fuzzy preference relations, consistent incomplete t-spherical fuzzy preference relations, and acceptable incomplete t-spherical fuzzy preference relations are established. Additionally, some ranking and selection algorithms are established using the proposed novel score function and preference relations to tackle the uncertainty in real-life decision-making problems. Finally, evaluation of the product quality of the online shopping platform problem is demonstrated to show the applicability and reliability of proposed technique. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IOS PRESS | - |
dc.title | Evaluation of the product quality of the online shopping platform using t-spherical fuzzy preference relations | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Choonkil | - |
dc.identifier.doi | 10.3233/JIFS-202930 | - |
dc.identifier.scopusid | 2-s2.0-85122014581 | - |
dc.identifier.wosid | 000731754900034 | - |
dc.identifier.bibliographicCitation | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, v.41, no.6, pp.6245 - 6262 | - |
dc.relation.isPartOf | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | - |
dc.citation.title | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | - |
dc.citation.volume | 41 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 6245 | - |
dc.citation.endPage | 6262 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.subject.keywordPlus | AGGREGATION OPERATORS | - |
dc.subject.keywordPlus | SETS | - |
dc.subject.keywordAuthor | Spherical fuzzy Sets | - |
dc.subject.keywordAuthor | t-spherical fuzzy set | - |
dc.subject.keywordAuthor | Improved operational laws | - |
dc.subject.keywordAuthor | Improved score function | - |
dc.subject.keywordAuthor | preference relations | - |
dc.subject.keywordAuthor | incomplete preference relations | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1365
COPYRIGHT © 2021 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.