Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/6717
Title: Comparative analysis of fuzzy inference systems for water consumption time series prediction
Authors: Fırat, Mahmut
Turan, Mustafa Erkan
Yurdusev, Mehmet Ali
Keywords: Adaptive neuro-fuzzy inference system
Mamdani fuzzy inference systems
Water consumption prediction
Water management
ANFIS model
Best-fit models
Comparative analysis
Fuzzy inference systems
Mamdani
Municipal water
Performance criterion
Prediction model
Time series prediction
Training and testing
Water consumption
Fuzzy inference
Mathematical models
Time series
Time series analysis
Water analysis
Water supply
Fuzzy systems
comparative study
fuzzy mathematics
hydrological modeling
prediction
time series
water management
water use
Abstract: Two 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.
URI: https://hdl.handle.net/11499/6717
https://doi.org/10.1016/j.jhydrol.2009.06.013
ISSN: 0022-1694
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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