Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/6717
Full metadata record
DC FieldValueLanguage
dc.contributor.authorFırat, Mahmut-
dc.contributor.authorTuran, Mustafa Erkan-
dc.contributor.authorYurdusev, Mehmet Ali-
dc.date.accessioned2019-08-16T12:09:57Z
dc.date.available2019-08-16T12:09:57Z
dc.date.issued2009-
dc.identifier.issn0022-1694-
dc.identifier.urihttps://hdl.handle.net/11499/6717-
dc.identifier.urihttps://doi.org/10.1016/j.jhydrol.2009.06.013-
dc.description.abstractTwo types of fuzzy inference systems (FIS) are used for predicting municipal water consumption time series. The FISs used include an adaptive neuro-fuzzy inference system (ANFIS) and a Mamdani fuzzy inference systems (MFIS). The prediction models are constructed based on the combination of the antecedent values of water consumptions. The performance of ANFIS and MFIS models in training and testing phases are compared with the observations and the best fit model is identified according to the selected performance criteria. The results demonstrated that the ANFIS model is superior to MFIS models and can be successfully applied for prediction of water consumption time series. © 2009 Elsevier B.V. All rights reserved.en_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Hydrologyen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAdaptive neuro-fuzzy inference systemen_US
dc.subjectMamdani fuzzy inference systemsen_US
dc.subjectWater consumption predictionen_US
dc.subjectWater managementen_US
dc.subjectANFIS modelen_US
dc.subjectBest-fit modelsen_US
dc.subjectComparative analysisen_US
dc.subjectFuzzy inference systemsen_US
dc.subjectMamdanien_US
dc.subjectMunicipal wateren_US
dc.subjectPerformance criterionen_US
dc.subjectPrediction modelen_US
dc.subjectTime series predictionen_US
dc.subjectTraining and testingen_US
dc.subjectWater consumptionen_US
dc.subjectFuzzy inferenceen_US
dc.subjectMathematical modelsen_US
dc.subjectTime seriesen_US
dc.subjectTime series analysisen_US
dc.subjectWater analysisen_US
dc.subjectWater supplyen_US
dc.subjectFuzzy systemsen_US
dc.subjectcomparative studyen_US
dc.subjectfuzzy mathematicsen_US
dc.subjecthydrological modelingen_US
dc.subjectpredictionen_US
dc.subjecttime seriesen_US
dc.subjectwater managementen_US
dc.subjectwater useen_US
dc.titleComparative analysis of fuzzy inference systems for water consumption time series predictionen_US
dc.typeArticleen_US
dc.identifier.volume374en_US
dc.identifier.issue3-4en_US
dc.identifier.startpage235
dc.identifier.startpage235en_US
dc.identifier.endpage241en_US
dc.identifier.doi10.1016/j.jhydrol.2009.06.013-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-68349089334en_US
dc.identifier.wosWOS:000269851000005en_US
dc.identifier.scopusqualityQ1-
dc.ownerPamukkale University-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.grantfulltextnone-
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

81
checked on Nov 16, 2024

WEB OF SCIENCETM
Citations

71
checked on Nov 21, 2024

Page view(s)

34
checked on Aug 24, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.