On‐Line Warning System for Pipe Burst Using Bayesian Dynamic Linear Models

Pipe breaks are a recurrent problem in water distribution networks and detecting them quickly is crucial to minimize the economic and environmental costs for municipalities. This study presents a burst detection methodology applying Bayesian dynamic linear models (DLMs) on water flow time series com...

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Veröffentlicht in:	Water resources research 2023-04, Vol.59 (4), p.n/a
Hauptverfasser:	Henriques‐Silva, Renato, Duchesne, Sophie, St‐Gelais, Nicolas Fortin, Saran, Naysan, Schmidt, Alexandra M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayes' factor Bayesian analysis Bayesian theory Data analysis Detection Distribution False alarms Mathematical models Model accuracy Modelling Monitoring Municipalities outlier detection Outliers (statistics) Pipes Probability theory time series analysis Warning systems Water distribution Water engineering Water flow Water supply systems
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