Outlier Detection in Predictive Analytics for Energy Equipment

  • Alexander AndryushinEmail author
  • Ivan Shcherbatov
  • Nina Dolbikova
  • Anna Kuznetsova
  • Grigory Tsurikov
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 259)


The method of data preprocessing used to predict the technical condition of power equipment is described. Preprocessing implemented using neural networks allows us to identify and eliminate outliers in the investigated data. An example illustrating the proposed method of processing big data using bagged trees algorithm, support vector machines and artificial neural networks is shown.


Predictive analytics system Energy Data preprocessing Neural network Bagged trees Support vector machines 



This work is supported by the Russian Science Foundation under grant № 19-19-00601.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Alexander Andryushin
    • 1
    Email author
  • Ivan Shcherbatov
    • 1
  • Nina Dolbikova
    • 1
  • Anna Kuznetsova
    • 1
  • Grigory Tsurikov
    • 1
  1. 1.Moscow Power Engineering InstituteMoscowRussia

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