Chapter
Apr 26, 2012
Real Time Assessment of Drinking Water Systems Using a Dynamic Bayesian Network
Authors: W. J. Dawsey [email protected], B. S. Minsker [email protected], and E. Amir [email protected]Author Affiliations
Publication: World Environmental and Water Resources Congress 2007: Restoring Our Natural Habitat
Abstract
This paper presents a methodology for real-time estimation of water distribution system state parameters using a dynamic Bayesian network to combine current observations with knowledge of past system behavior. The dynamic Bayesian network presented here allows the flexibility to model both discrete and continuous variables and represent causal relationships that exist within the distribution system. The posterior belief state can be inferred using a compact approximation algorithm that has been shown to contain inference errors. Simulations over stochastic variables are proposed to define the transition and observation models for the dynamic Bayesian network.
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© 2007 American Society of Civil Engineers.
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Published online: Apr 26, 2012
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Graduate, Research Asst., Dept of Civil & Environmental Engineering, University of Illinois-Urbana, 205. N. Mathews Ave, Urbana, IL 61801. E-mail: [email protected]
Professor, Dept of Civil & Environmental Engineering, University of Illinois-Urbana, 205. N. Mathews Ave, Urbana, IL 61801. E-mail: [email protected]
Assistant Professor, Dept of Computer Science, University of Illinois-Urbana, 201 N Goodwin Ave, Urbana, IL 61801. E-mail: [email protected]
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