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Modeling Procedure to Adapt to Change of Trend of Water Demand: Application of Bayesian Parameter Estimation  

Lee, Sangeun (KAIST 응용과학연구소)
Park, Heekyung (KAIST 건설및환경공학과)
Publication Information
Journal of Korean Society of Water and Wastewater / v.23, no.2, 2009 , pp. 241-249 More about this Journal
Abstract
It is well known that the trend of water demand in large-size water supply systems has been suddenly changed, and many expansions of water supply facilities become unnecessary. To be cost-effective, thus, politicians as well as many professionals lay stress on the adaptive management of water supply facilities. Failure in adapting to the new trend of demand is sure to be the most critical reason of unnecessary expansions. Hence, we try to develop the model and modeling procedure that do not depend on the old data of demand, and provide engineers with the fast learning process. To forecast water demand of Seoul, the Bayesian parameter estimation was applied, which is a representative method for statistical pattern recognition. It results that we can get a useful time-series model after observing water demand during 6 years, although trend of water demand were suddenly changed.
Keywords
overcapacity; water treatment plants; trend of water demand; Bayesian Parameter Estimation;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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