Routine forecasting of the daily profiles of hourly water distribution in cities. An effectiveness analysis

• Autorzy: Cieżak W. , Cieżak J.

Identyfikatory

DOI

10.5277/epe150215

• Języki publikacji: EN

Abstrakty

EN

Sample results have been oresented of verifying three groups of methods of forecasting the time series of short-duration water distributions in city water grids. The analysis covered: ARIMA class models, the time series exponential smoothing methods and artificial neural networks. Since chronological sequences of observations from the immediate past were analyzed, the adopted models did not take any external variables into account. The forecasting errors in the case of multilayer perceptron neural networks were found to be comparable or smaller than the errors of prediction by the ARIMA class models and by the methods of the exponential smoothing of time series.

Słowa kluczowe

EN

forecasting; multilayer neural networks; neural networks; time series; water supply system; water distribution

PL

prognozowanie; wielowarstwowe sieci neuronowe; sieci neuronowe; szereg czasowy; wodociągi; dystrybucja wody

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Environment Protection Engineering
• Rocznik: 2015
• Tom: Vol. 41, nr 2
• Strony: 179--186
• Opis fizyczny: Bibliogr. 10 poz., tab., rys.

Twórcy

autor

Cieżak W.

• Wrocław University of Technology, Faculty of Environmental Engineering, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

autor

Cieżak J.

• Wrocław University of Technology, Faculty of Environmental Engineering, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland

Bibliografia

• [1] SIWOŃ Z., ŁOMOTOWSKI J., CIEŻAK W., LICZNAR P., CIEŻAK J., Analysis and forecasting of water distributions in water supply systems, Polish Academy of Sciences, Civil Engineering Committee, Institute of Fundamental Technological Research, Studies in Engineering, No. 61, Warsaw 2008 (in Polish).
• [2] SIWOŃ Z., CIEŻAK W., CIEŻAK J., Neural models of time series of hourly water intake in housing estates, Ochr. Środ., 2011, 33 (2), 23 (in Polish).
• [3] ROMANO M., KAPELAN Z., Adaptive water demand forecasting for near real-time management of smart water distribution systems, Environ. Modell. Softw., 2014, 60, 265.
• [4] KUTYŁOWSKA M., HOTLOŚ H., Failure analysis of water supply system in the Polish city of Głogów, Eng. Fail. Anal., 2014, 41, 23.
• [5] KOTOWSKI A., Hydraulic analysis of phenomena reducing pipeline flowability, Ochr. Środ., 2010, 32 (1), 27 (in Polish).
• [6] KĘPA U., STAŃCZYK-MAZANEK E., A hydraulic model as a useful tool in the operation of a waterpipe network, Polish J. Environ. Stud., 2014, 23 (3), 995.
• [7] NYENDE-BYAKIKAA S., NGIRANE-KATASHAYAB G., NDAMBUKIA J.M., Application of hydraulic modelling to control intrusion into potable water pipelines, Urban Wat. J., 2013, 10 (3), 216.
• [8] HABIB A.M., SADEGH R., SARALEES N., MAHSA E., Estimation of water demand in Iran based on SARIMA models, Environ. Modell. Assess., 2013, 18, 559.
• [9] HERRERA M., TORGO L., IZQUIERDO J., PÉREZ-GARCIA R., Predictive models for forecasting hourly urban water demand, J. Hydrol., 2010, 387, 141.
• [10] HUTTON C.J., KAPELAN Z., A probabilistic methodology for quantifying, diagnosing and reducing model structural and predictive errors in short term water demand forecasting, Environ. Modell. Softw., 2015, 66, 87.