Estimation of fuzzy anomalies in Water Distribution Systems

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dc.creatorIzquierdo, J.
dc.creatorTung, M. M.
dc.creatorPerez, R.
dc.creatorMartinez, F. J.
dc.date2007-11-19
dc.date.accessioned2026-07-07T08:43:43Z
dc.date.available2026-07-07T08:43:43Z
dc.descriptionState estimation is necessary in diagnosing anomalies in Water Demand Systems (WDS). In this paper we present a neural network performing such a task. State estimation is performed by using optimization, which tries to reconcile all the available information. Quantification of the uncertainty of the input data (telemetry measures and demand predictions) can be achieved by means of robust estate estimation. Using a mathematical model of the network, fuzzy estimated states for anomalous states of the network can be obtained. They are used to train a neural network capable of assessing WDS anomalies associated with particular sets of measurements.
dc.description5 pages
dc.identifierhttps://arxiv.org/abs/0711.2897
dc.identifierhttp://arxiv.org/abs/0711.2897
dc.identifierProgress in Industrial Mathematics at ECMI 2006 (edited by L. L. Bonilla, M. A. Moscoso, G. Platero, and J. M. Vega), vol. 12 of Mathematics in Industry, pp. 801-805 (Springer, Berlin, 2007), ISBN 978-3-540-71991-5
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/142417
dc.subjectNeural and Evolutionary Computing
dc.subjectI.5.1
dc.titleEstimation of fuzzy anomalies in Water Distribution Systems
dc.typetext

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