On the nearest parametric approximation of a fuzzy number
| dc.contributor.author | Efendi N. Nasibov | |
| dc.contributor.author | Sinem Peker | |
| dc.date.accessioned | 2025-10-06T17:53:15Z | |
| dc.date.issued | 2008 | |
| dc.description.abstract | Many nearest parametric approximation methods of fuzzy sets are proposed in the literature. It is clear that the specific approximations may lead to the loss of information about fuzziness. To overcome this problem most of these methods rely on the minimization of the distance between the original fuzzy set and its approximation. But these approximations mostly are not flexible to the decision maker's choice. Hence in this paper we offer a parametric fuzzy approximation method based on the decision maker's strategy as an extension of trapezoidal approximation of a fuzzy number. This method comprises the selection of the form of the parametric membership function and its evaluation. © 2007 Elsevier B.V. All rights reserved. © 2008 Elsevier B.V. All rights reserved. | |
| dc.identifier.doi | 10.1016/j.fss.2007.08.005 | |
| dc.identifier.issn | 01650114 | |
| dc.identifier.issn | 0165-0114 | |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-41549117955&doi=10.1016%2Fj.fss.2007.08.005&partnerID=40&md5=3bb36ef7b134935271e865c5515714e8 | |
| dc.identifier.uri | https://gcris.yasar.edu.tr/handle/123456789/10355 | |
| dc.language.iso | English | |
| dc.relation.ispartof | Fuzzy Sets and Systems | |
| dc.source | Fuzzy Sets and Systems | |
| dc.subject | Defuzzification, Fuzzy Distance, Fuzzy Number, Nearest Approximation, Approximation Theory, Decision Making, Fuzzy Sets, Parameter Estimation, Fuzzy Distance, Fuzzy Number, Nearest Approximation, Number Theory | |
| dc.subject | Approximation theory, Decision making, Fuzzy sets, Parameter estimation, Fuzzy distance, Fuzzy number, Nearest approximation, Number theory | |
| dc.title | On the nearest parametric approximation of a fuzzy number | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| gdc.bip.impulseclass | C4 | |
| gdc.bip.influenceclass | C4 | |
| gdc.bip.popularityclass | C4 | |
| gdc.coar.type | text::journal::journal article | |
| gdc.collaboration.industrial | false | |
| gdc.description.endpage | 1375 | |
| gdc.description.startpage | 1365 | |
| gdc.description.volume | 159 | |
| gdc.identifier.openalex | W2088918677 | |
| gdc.index.type | Scopus | |
| gdc.oaire.diamondjournal | false | |
| gdc.oaire.impulse | 17.0 | |
| gdc.oaire.influence | 6.7206707E-9 | |
| gdc.oaire.isgreen | true | |
| gdc.oaire.keywords | fuzzy number | |
| gdc.oaire.keywords | defuzzification | |
| gdc.oaire.keywords | nearest approximation | |
| gdc.oaire.keywords | fuzzy distance | |
| gdc.oaire.keywords | Theory of fuzzy sets, etc. | |
| gdc.oaire.keywords | Reasoning under uncertainty in the context of artificial intelligence | |
| gdc.oaire.keywords | Decision theory | |
| gdc.oaire.popularity | 1.1379957E-8 | |
| gdc.oaire.publicfunded | false | |
| gdc.oaire.sciencefields | 0202 electrical engineering, electronic engineering, information engineering | |
| gdc.oaire.sciencefields | 02 engineering and technology | |
| gdc.openalex.collaboration | National | |
| gdc.openalex.fwci | 7.5266 | |
| gdc.openalex.normalizedpercentile | 0.97 | |
| gdc.openalex.toppercent | TOP 10% | |
| gdc.opencitations.count | 58 | |
| gdc.plumx.crossrefcites | 39 | |
| gdc.plumx.mendeley | 11 | |
| gdc.plumx.scopuscites | 67 | |
| oaire.citation.endPage | 1375 | |
| oaire.citation.startPage | 1365 | |
| person.identifier.scopus-author-id | Nasibov- Efendi N. (56007375900), Peker- Sinem (23991127300) | |
| publicationissue.issueNumber | 11 | |
| publicationvolume.volumeNumber | 159 | |
| relation.isOrgUnitOfPublication | ac5ddece-c76d-476d-ab30-e4d3029dee37 | |
| relation.isOrgUnitOfPublication.latestForDiscovery | ac5ddece-c76d-476d-ab30-e4d3029dee37 |
