Forecasting Domestic Water Consumption Using Bayesian Model

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 57)

Abstract

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.

Keywords

Forecasting time series Domestic water consumption Bayesian networks 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute of Computer Science, University of SilesiaSosnowiecPoland

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