For the optimal operation of waterworks it is necessary to predict the expected water consumption of the following days as accurately as possible. However, there are no conventional methods to predict the water demand. In this paper a prediction model based on hybrid fuzzy algorithms is introduced. The software automatically creates a fuzzy rule system out of a training database using the so-called VISIT (Variable Input Spread Inference Training) algorithm. A fuzzy neural network (FNN) system is created. Rules are trained with back propagation (BP) and least squares estimate (LSE) methods. The parameters of the algorithm are optimized with a simple genetic algorithm. As a result, one gets a rule system that delivers higher accuracy than a common statistically based model. Calculations and results are presented in this paper.
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Research Article|
May 01 2009
Prognosis of urban water consumption using hybrid fuzzy algorithms
Gergely Bárdossy
;
1
Department of Hydrodynamic Systems, Budapest University of Technology and Economics, Mûegyetem rkp. 3, Budapest, 1111, Hungary
Tel.: +36 1 463 3097 Fax.: +36 1 463 3091; E-mail: bardossy@hds.bme.hu
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Gábor Halász
;
Gábor Halász
1
Department of Hydrodynamic Systems, Budapest University of Technology and Economics, Mûegyetem rkp. 3, Budapest, 1111, Hungary
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János Winter
János Winter
2
Department of Hydraulic and Water Resources Engineering, Budapest University of Technology and Economics, Mûegyetem rkp. 3, Budapest, 1111, Hungary
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Journal of Water Supply: Research and Technology-Aqua (2009) 58 (3): 203-211.
Article history
Received:
August 28 2007
Accepted:
November 07 2008
Citation
Gergely Bárdossy, Gábor Halász, János Winter; Prognosis of urban water consumption using hybrid fuzzy algorithms. Journal of Water Supply: Research and Technology-Aqua 1 May 2009; 58 (3): 203–211. doi: https://doi.org/10.2166/aqua.2009.092
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Gergely Bárdossy, Gábor Halász, János Winter; Prognosis of urban water consumption using hybrid fuzzy algorithms. Journal of Water Supply: Research and Technology-Aqua 1 May 2009; 58 (3): 203–211. doi: https://doi.org/10.2166/aqua.2009.092
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