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Automation and Remote Control

, Volume 73, Issue 6, pp 1075–1084 | Cite as

Using connectionist systems for electric energy consumption forecasting in shopping centers

  • V. A. Kamaev
  • M. V. Shcherbakov
  • D. P. Panchenko
  • N. L. Shcherbakova
  • A. Brebels
Large Scale Systems Control

Abstract

A solution is presented for the short-term electrical energy forecasting in shopping centers located in the Netherlands and Belgium. A forecasting method is proposed on the basis of connectionist systems. General description of the forecasting method is provided, as well as its specific features with respect to the forecasting problem are studied. Several connectionist models are generalized, stated and applied, notably, moving average model, linear regression model, and neural network model. In addition, changes in forecasting quality are demonstrated depending on different input variables. The results of using these connectionist models are discussed, and conclusions regarding specific features of every model are outlined.

Keywords

Energy Consumption Remote Control Linear Regression Model Forecast Error Mean Absolute Percentage Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Pleiades Publishing, Ltd. 2012

Authors and Affiliations

  • V. A. Kamaev
    • 1
  • M. V. Shcherbakov
    • 1
  • D. P. Panchenko
    • 1
  • N. L. Shcherbakova
    • 1
  • A. Brebels
    • 2
  1. 1.State Technical UniversityVolgogradRussia
  2. 2.Katholieke Hogeschool KempenGeelBelgium

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