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   <dc:title>Short-term demand forecasting for real-time operational control of the Barcelona water transport network</dc:title>
   <dc:creator>Quevedo Casín, Joseba Jokin</dc:creator>
   <dc:creator>Saludes Closa, Jordi</dc:creator>
   <dc:creator>Puig Cayuela, Vicenç</dc:creator>
   <dc:creator>Blanch i Font, Jordi</dc:creator>
   <dc:contributor>Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial</dc:contributor>
   <dc:contributor>Universitat Politècnica de Catalunya. Departament de Matemàtica Aplicada II</dc:contributor>
   <dc:contributor>Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control</dc:contributor>
   <dc:contributor>Universitat Politècnica de Catalunya. SIC - Sistemes Intel·ligents de Control</dc:contributor>
   <dc:subject>Àrees temàtiques de la UPC::Informàtica::Automàtica i control</dc:subject>
   <dc:subject>Exponential smoothing methods</dc:subject>
   <dc:subject>Short-term forecasting</dc:subject>
   <dc:subject>Internal model control</dc:subject>
   <dc:subject>Automation</dc:subject>
   <dc:subject>Aigua -- Abastament -- Gestió</dc:subject>
   <dc:subject>Automatització</dc:subject>
   <dc:description>This paper focuses on the forecast of the hourly&#xd;
water demand data of distinct pressure floors of the Barcelona&#xd;
water transport network. Several methods to forecast the&#xd;
hourly water demand are studied and compared with the aim&#xd;
of being applied for the operational control of the Barcelona&#xd;
water transport network. The short-term forecast of the&#xd;
intraday series has a main feature: the double periodicity (daily&#xd;
and hourly). To address this issue several extensions of the&#xd;
classical time-series forecasting methods are proposed: seasonal&#xd;
ARIMA, structural models and the exponential methods&#xd;
without external information. The paper focuses on the daily&#xd;
and hourly forecasts. In the hourly forecast, the exponential&#xd;
smoothing method is the most accurate. On the hand, the&#xd;
seasonal ARIMA and the exponential smoothing are similar in&#xd;
the daily time scale.</dc:description>
   <dc:description>Peer Reviewed</dc:description>
   <dc:description>Postprint (published version)</dc:description>
   <dc:date>2014</dc:date>
   <dc:type>Conference report</dc:type>
   <dc:identifier>Quevedo, J. [et al.]. Short-term demand forecasting for real-time operational control of the Barcelona water transport network. A: Mediterranean Conference on Control &amp; Automation. "2014 22nd Mediterranean Conference on Control and Automation (MED) University of Palermo. June 16-19, 2014. Palermo, Italy". Palermo: 2014, p. 990-995.</dc:identifier>
   <dc:identifier>https://hdl.handle.net/2117/24350</dc:identifier>
   <dc:identifier>978-1-4799-5899-3/14/$31.00 ©2014 IEEE</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:rights>Restricted access - publisher's policy</dc:rights>
   <dc:format>6 p.</dc:format>
   <dc:format>application/pdf</dc:format>
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