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Forecasting Daily Water Demand Using Fuzzy Cognitive Maps

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Time Series Analysis and Forecasting

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

Abstract

In this chapter, we describe the design of a multi-regressive forecasting model based on fuzzy cognitive maps (FCMs). Growing window approach and 1-day ahead forecasting are assumed. The proposed model is retrained every day as more data become available. To improve forecasting accuracy, mean daily temperature and precipitation are applied as additional explanatory variables. The designed model is trained and tested using data gathered from a water distribution system. Comparative experiments provide evidence for the superiority of the proposed approach over the selected state-of-the-art competitive methods.

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Acknowledgements

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. The authors would like to thank the water distribution company in Sosnowiec (Poland) for gathering water demand data and the personal of the weather station of the University of Silesia for collecting and preparing meteorological data.

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Authors and Affiliations

  1. University Pablo de Olavide, Seville, Spain

    Jose L. Salmeron

  2. The University of Silesia, ul. Bedzinska 39, Sosnowiec, Poland

    Wojciech Froelich

  3. Computer Engineering Department, Technological Educational Institute of Central Greece, 3o Km Old National Road Lamia-Athens, TK, 35100, Lamia, Greece

    Elpiniki I. Papageorgiou

Authors
  1. Jose L. Salmeron
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  2. Wojciech Froelich
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  3. Elpiniki I. Papageorgiou
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Corresponding author

Correspondence to Jose L. Salmeron .

Editor information

Editors and Affiliations

  1. CITIC-UGR, University of Granada, Granada, Spain

    Ignacio Rojas

  2. CITIC-UGR, University of Granada, Granada, Spain

    Héctor Pomares

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Salmeron, J.L., Froelich, W., Papageorgiou, E.I. (2016). Forecasting Daily Water Demand Using Fuzzy Cognitive Maps. In: Rojas, I., Pomares, H. (eds) Time Series Analysis and Forecasting. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-28725-6_24

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