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Urban water demand forecasting for the Island of skiathos

dc.creatorKofinas, D.en
dc.creatorMellios, N.en
dc.creatorPapageorgiou, E.en
dc.creatorLaspidou, C.en
dc.date.accessioned2015-11-23T10:35:07Z
dc.date.available2015-11-23T10:35:07Z
dc.date.issued2014
dc.identifier10.1016/j.proeng.2014.11.220
dc.identifier.issn18777058
dc.identifier.urihttp://hdl.handle.net/11615/29510
dc.description.abstractWe present an analysis of historical water demand data from the utility of Skiathos, Greece and demonstrate suitable demand forecasting methodologies. We apply linear and nonlinear forecasting methods to a three-year time series water demand. The best fit for quarterly averaged data was observed for the Winters' additive method; for monthly-averaged data, ARIMA, Artificial Neural Network and a hybrid approach performed best. Given the intense seasonality of demand in Skiathos, monthly time series proved to be the best data set for forecasting, while the best forecasting method was the hybrid, which combines the advantages of ARIMA and Artificial Neural Networks. © 2014 The Authors.en
dc.source.urihttp://www.scopus.com/inward/record.url?eid=2-s2.0-84923095095&partnerID=40&md5=fb38a28fa150fa3ce41bf136da1f7ab1
dc.subjectARIMAen
dc.subjectArtificial neural networksen
dc.subjectForecastingen
dc.subjectTime seriesen
dc.subjectUrban water demanden
dc.subjectWater distribution networksen
dc.subjectNeural networksen
dc.subjectWater supply systemsen
dc.subjectSystems analysisen
dc.subjectAdditive methodsen
dc.subjectDemand forecastingen
dc.subjectForecasting methodsen
dc.subjectHybrid approachen
dc.subjectNonlinear forecastingen
dc.subjectUrban watersen
dc.subjectWater distribution systemsen
dc.titleUrban water demand forecasting for the Island of skiathosen
dc.typeconferenceItemen


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