| dc.contributor.author | Köseoğlu, Ali | |
| dc.contributor.author | Şahin, Rıdvan | |
| dc.date.accessioned | 2024-09-29T14:30:52Z | |
| dc.date.available | 2024-09-29T14:30:52Z | |
| dc.date.issued | 2024 | en_US |
| dc.identifier.citation | Scopus
EXPORT DATE: 29 September 2024
@ARTICLE{Köseoğlu2024707,
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203603736&doi=10.1007%2f978-3-031-70018-7_78&partnerID=40&md5=6ab683db932c219ef7bd7832afca716b},
affiliations = {Faculty of Arts and Sciences, Department of Mathematics, Recep Tayyip Erdogan University, Rize, Turkey; Engineering and Natural Sciences Faculty, Department of Software Engineering, Gumushane University, Gümüşhane, Turkey},
correspondence_address = {A. Köseoğlu; Faculty of Arts and Sciences, Department of Mathematics, Recep Tayyip Erdogan University, Rize, Turkey; email: ali.koseoglu@erdogan.edu.tr},
editor = {Kahraman C. and Cevik Onar S. and Cebi S. and Oztaysi B. and Ucal Sari I. and Tolga A.C.},
publisher = {Springer Science and Business Media Deutschland GmbH},
issn = {23673370},
isbn = {978-303170017-0},
language = {English},
abbrev_source_title = {Lect. Notes Networks Syst.}
} | en_US |
| dc.identifier.uri | https://www.scopus.com/record/display.uri?eid=2-s2.0-85203603736&origin=SingleRecordEmailAlert&dgcid=raven_sc_affil_en_us_email&txGid=5d6e0af8ea5259adba16420b4ce4d8ab | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12440/6324 | |
| dc.description.abstract | Fuzzy sets allow elements to have partial membership in a set, represented by a membership value between 0 and 1. This feature enables fuzzy sets to model imprecise or vague concepts. Decomposed fuzzy sets, an extension of fuzzy sets, have introduced a novel perspective in the literature by incorporating the Kano model into risk assessment. These sets have also paved the way for new approaches in decision-making methods, highlighting their functional and dysfunctional elements. In this paper, we propose a distance measure for decomposed fuzzy sets and subsequently extend the TODIM method based on this distance measure to DFSs. Then, we provide a numerical example to illustrate its effectiveness and practicality. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Springer Science and Business Media Deutschland GmbH | en_US |
| dc.relation.ispartof | Lecture Notes in Networks and Systems | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Decomposed Fuzzy Sets; Distance Measures; TODIM method | en_US |
| dc.title | Extension of TODIM Method Based on Distance Measures of Decomposed Fuzzy Sets | en_US |
| dc.type | conferenceObject | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümü | en_US |
| dc.authorid | 0000-0001-7434-4269 | en_US |
| dc.identifier.volume | 1088 LNNS | en_US |
| dc.identifier.startpage | 707 | en_US |
| dc.contributor.institutionauthor | Şahin, Rıdvan | |
| dc.identifier.doi | 10.1007/978-3-031-70018-7_78 | en_US |
| dc.identifier.endpage | 714 | en_US |
| dc.authorscopusid | 56285350800 | en_US |
