Searched for: subject%3A%22water%255C%252Bdemand%255C%252Bforecasting%22
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Xenochristou, Maria (author), Hutton, Chris (author), Hofman, Jan (author), Kapelan, Z. (author)This study utilizes a rich UK data set of smart demand metering data, household characteristics, and weather data to develop a demand forecasting methodology that combines the high accuracy of machine learning models with the interpretability of statistical methods. For this reason, a random forest model is used to predict daily demands 1 day...journal article 2021
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Xenochristou, Maria (author), Kapelan, Z. (author)Water demand forecasting is an essential task for water utilities, with increasing importance due to future societal and environmental changes. This paper suggests a new methodology for water demand forecasting, based on model stacking and bias correction that predicts daily demands for groups of ~120 properties. This methodology is compared...journal article 2020