Short-Term Forecasting of Household Water Demand in the UK Using an Interpretable Machine-Learning Approach

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...