- document
-
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
- document
-
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