Comparative analysis of fuzzy inference systems for water consumption time series prediction

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dc.contributor.authorFirat M.
dc.contributor.authorTuran M.E.
dc.contributor.authorYurdusev M.A.
dc.date.accessioned2024-07-22T08:21:38Z
dc.date.available2024-07-22T08:21:38Z
dc.date.issued2009
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.
dc.identifier.DOI-ID10.1016/j.jhydrol.2009.06.013
dc.identifier.issn00221694
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/18708
dc.language.isoEnglish
dc.subjectFuzzy inference
dc.subjectMathematical models
dc.subjectTime series
dc.subjectTime series analysis
dc.subjectWater analysis
dc.subjectWater management
dc.subjectWater supply
dc.subjectAdaptive neuro-fuzzy inference system
dc.subjectANFIS model
dc.subjectBest-fit models
dc.subjectComparative analysis
dc.subjectFuzzy inference systems
dc.subjectMamdani
dc.subjectMamdani fuzzy inference systems
dc.subjectMunicipal water
dc.subjectPerformance criterion
dc.subjectPrediction model
dc.subjectTime series prediction
dc.subjectTraining and testing
dc.subjectWater consumption
dc.subjectWater consumption prediction
dc.subjectcomparative study
dc.subjectfuzzy mathematics
dc.subjecthydrological modeling
dc.subjectprediction
dc.subjecttime series
dc.subjectwater management
dc.subjectwater use
dc.subjectFuzzy systems
dc.titleComparative analysis of fuzzy inference systems for water consumption time series prediction
dc.typeArticle

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