Adaptive neuro fuzzy inference system approach for municipal water consumption modeling: An application to Izmir, Turkey
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Date
2009
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Abstract
In this study, an adaptive neuro fuzzy inference system (ANFIS) is used to forecast monthly water use from several socio-economic and climatic factors including average monthly water bill, population, number of households, gross national product, monthly average temperature observed, monthly total rainfall, monthly average humidity observed and inflation rate. Water consumption modeling in this way will be more consistent than doing it using a single variable as more effective parameter could be incorporated. The ANFIS system is applied to modeling monthly water consumptions of Izmir, Turkey. The results indicated that ANFIS can be successfully applied for monthly water consumption modeling. © 2008 Elsevier B.V. All rights reserved.
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Eurasia , Izmir [Turkey] , Turkey , Backpropagation , Economics , Fuzzy inference , Fuzzy logic , Fuzzy sets , Population statistics , Water supply , artificial neural network , climate effect , forecasting method , fuzzy mathematics , hydrological modeling , water demand , water use , ANFIS , ANN , Prediction , Water consumption , Water demand , Fuzzy systems