A Comparison of Short Term Forecast Methods for Municipal Water Useby Ashu Jain, Univ of Kentucky, Lexington, United States,
Lindell Ormsbee, Univ of Kentucky, Lexington, United States,
Abstract: Water utilities routinely develop long range demand forecasts for use in the normal planning activities. In recent years, many utilities have sought to develop more short-term demand forecasts for use in daily operations. In the current study three different short-term (daily) demand models are developed and tested for the city of Lexington, Kentucky. Developed models include a lumped response model, a distributed response model, and a neural network based model.
Subject Headings: Municipal water | Mathematical models | Forecasting | Water use | Comparative studies | Model analysis | Water demand | Neural networks | Water supply systems | Model tests | Lifeline systems | North America | Kentucky | United States
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