7 research outputs found
Enhanced water demand analysis via symbolic approximation within an epidemiology-based forecasting framework
Epidemiology-based models have shown to have successful adaptations to deal with challenges coming from various areas of Engineering, such as those related to energy use or asset management. This paper deals with urban water demand, and data analysis is based on an Epidemiology tool-set herein developed. This combination represents a novel framework in urban hydraulics. Specifically, various reduction tools for time series analyses based on a symbolic approximate (SAX) coding technique able to deal with simple versions of data sets are presented. Then, a neural-network-based model that uses SAX-based knowledge-generation from various time series is shown to improve forecasting abilities. This knowledge is produced by identifying water distribution district metered areas of high similarity to a given target area and sharing demand patterns with the latter. The proposal has been tested with databases from a Brazilian water utility, providing key knowledge for improving water management and hydraulic operation of the distribution system. This novel analysis framework shows several benefits in terms of accuracy and performance of neural network models for water demand112sem informaçãosem informaçã
Enhanced Water Demand Analysis via Symbolic Approximation within an Epidemiology-Based Forecasting Framework
[EN] Epidemiology-based models have shown to have successful adaptations to deal with challenges coming from various areas of Engineering, such as those related to energy use or asset management. This paper deals with urban water demand, and data analysis is based on an Epidemiology tool-set herein developed. This combination represents a novel framework in urban hydraulics. Specifically, various reduction tools for time series analyses based on a symbolic approximate (SAX) coding technique able to deal with simple versions of data sets are presented. Then, a neural-network-based model that uses SAX-based knowledge-generation from various time series is shown to improve forecasting abilities. This knowledge is produced by identifying water distribution district metered areas of high similarity to a given target area and sharing demand patterns with the latter. The proposal has been tested with databases from a Brazilian water utility, providing key knowledge for improving water management and hydraulic operation of the distribution system. This novel analysis framework shows several benefits in terms of accuracy and performance of neural network models for water demand.Navarrete-López, CF.; Herrera Fernández, AM.; Brentan, BM.; Luvizotto Jr., E.; Izquierdo Sebastián, J. (2019). Enhanced Water Demand Analysis via Symbolic Approximation within an Epidemiology-Based Forecasting Framework. Water. 11(246):1-17. https://doi.org/10.3390/w11020246S11711246Fecarotta, O., Carravetta, A., Morani, M., & Padulano, R. (2018). Optimal Pump Scheduling for Urban Drainage under Variable Flow Conditions. Resources, 7(4), 73. doi:10.3390/resources7040073Creaco, E., & Pezzinga, G. (2018). Comparison of Algorithms for the Optimal Location of Control Valves for Leakage Reduction in WDNs. Water, 10(4), 466. doi:10.3390/w10040466Nguyen, K. A., Stewart, R. 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SAX-quantile based multiresolution approach for finding heatwave events in summer temperature time series
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Gestión inteligente de sistemas de distribución de agua
The United Nations predicts that the world's population in 2050 will reach 9.7 billion people. This exponential growth will mean an increase in the global demand for water available for human consumption. In addition, the advance of climate change is causing the occurrence of more frequent droughts, especially in arid and semi-arid areas. Indirectly, this means an increase in the costs associated with water transport and purification, as water must be drawn from sources that are increasingly distant from the points of consumption and the quality is getting worse. The traditional management of urban water supply is changing towards a more sustainable model aimed at an efficient use of resources (water, energy, labour) that not only reduces management costs but is also more environmentally friendly. 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El nodo de comunicación desarrollado ad-hoc para este trabajo, envía los datos de la presión del agua a la nube, donde los usuarios pueden visualizarlos con un dispositivo con conexión a internet. Entre sus ventajas están su bajo coste, permite el uso de diferentes sistemas de comunicación y tiene una gran autonomía alimentada por baterías, lo que hace que se adapte bien a los sistemas de abastecimiento. El sistema de monitorización propuesto detecta fallos en la red por caídas de presión, alertando a los gestores de la zona afectada. El capítulo 5 explica la herramienta de apoyo a la toma de decisiones desarrollada para hacer frente a las averías en las redes de abastecimiento en alta. La plataforma web, que soporta esta herramienta, se divide en 3 módulos independientes: detección de averías, alertas y reparación de averías. 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