Comparative analysis of fuzzy inference systems for water consumption time series prediction
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Green Open Access
Yes
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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.
Description
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, Adaptive neuro-fuzzy inference system, Time series, 330, Time series analysis, ANFIS model, Time series prediction, water use, Mamdani, hydrological modeling, Performance criterion, Water supply, Water consumption, Prediction model, water management, Training and testing, fuzzy mathematics, Best-fit models, comparative study, Municipal water, Mathematical models, Mamdani fuzzy inference systems, Water consumption prediction, Comparative analysis, Fuzzy systems, prediction, Fuzzy inference systems, Water analysis, Water management, Fuzzy inference, time series
Fields of Science
0208 environmental biotechnology, 0207 environmental engineering, 02 engineering and technology
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OpenCitations Citation Count
83
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Volume
374
Issue
3-4
Start Page
235
End Page
241
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Scopus : 82
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