Forecasting Domestic Water Consumption Using Bayesian Model
In this paper, we address the problem of forecasting domestic water consumption. A specific feature of the forecasted time series is that water consumption occurs at random time steps. This substantially limits the application of the standard state-of-the art forecasting methods. The other existing forecasting models dedicated to predicting water consumption in households rely on data collected from questionnaires or diaries, requiring additional effort for gathering data. To overcome those limitations, we propose in this paper a Bayesian model to be applied for the forecasting of the domestic water consumption time series. The proposed theoretical approach has been tested using real-world data gathered from an anonymous household.
KeywordsForecasting time series Domestic water consumption Bayesian networks
The work was supported by ISS-EWATUS project which has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 619228.
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