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K N O W L E D G E D I S C O V E R Y Applying Knowledge

Summary: K N O W L E D G E D I S C O V E R Y
Applying Knowledge
Discovery to Predict
Water-Supply Consumption
Aijun An, Christine Chan, Ning Shan, Nick Cercone, and Wojciech Ziarko,
University of Regina, Saskatchewan, Canada
ations in a municipal water-distribution sys-
tem can reduce electricity costs and realize
other economic benefits. However, optimal
control requires an ability to precisely predict
short-term water demand so that minimum-
cost pumping schedules can be prepared. One
of the objectives of our project to develop an
intelligent system for monitoring and con-
trolling municipal water-supply systems is to
ensure optimal control and reduce energy
costs. Hence, prediction of water demand is
essential. In this article, we present an appli-
cation of a rough-set approach for automated


Source: An, Aijun - Department of Computer Science, York University (Toronto)


Collections: Computer Technologies and Information Sciences