Hybrid Adaptive Systems of Computational Intelligence and Their On-line Learning for Green IT in Energy Management Tasks

  • Yevgeniy BodyanskiyEmail author
  • Olena Vynokurova
  • Iryna Pliss
  • Dmytro Peleshko
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 74)


In this book chapter, we have considered a topical problem of intelligent energy management, which arises in the context of an intensively developed science direction—Green IT. The hybrid neuro-neo-fuzzy system and its high-speed learning algorithm are proposed. This system can be used for on-line prediction of essentially non-stationary nonlinear chaotic and stochastic time series, which describe electrical load producing and consuming processes. The considered hybrid adaptive system of computational intelligence has some advantages over the conventional artificial neural networks and neuro-fuzzy systems. The proposed hybrid neuro-neo-fuzzy prediction system provides a high quality load prediction that is very important for power systems.


Computational intelligence On-line learning Green IT Hybrid adaptive systems Neuro-neo-fuzzy system  


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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Yevgeniy Bodyanskiy
    • 1
    Email author
  • Olena Vynokurova
    • 1
  • Iryna Pliss
    • 1
  • Dmytro Peleshko
    • 2
  1. 1.Kharkiv National University of Radio ElectronicsKharkivUkraine
  2. 2.Lviv Politechnic National UniversityLvivUkraine

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