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The Concept on Nonlinear Modelling of Dynamic Objects Based on State Transition Algorithm and Genetic Programming

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Artificial Intelligence and Soft Computing (ICAISC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10246))

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Abstract

In this paper a new hybrid method to determine parameters of time-variant non-linear models of dynamic objects is proposed. This method first uses the State Transition Algorithm to create many local models and then applies genetic programming in order to join and simplify those models. This allows to obtain simply model which is not computationally demanding and has high accuracy.

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Acknowledgment

The project was financed by the National Science Center on the basis of the decision number DEC-2012/05/B/ST7/02138.

Author information

Authors and Affiliations

  1. Institute of Computational Intelligence, Częstochowa University of Technology, Częstochowa, Poland

    Łukasz Bartczuk & Piotr Dziwiński

  2. Scientific Research Institute for System Analysis of the Russian Academy of Sciences, Moscow, Russia

    Vladimir G. Red’ko

Authors
  1. Łukasz Bartczuk
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  2. Piotr Dziwiński
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  3. Vladimir G. Red’ko
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Corresponding author

Correspondence to Łukasz Bartczuk .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Bartczuk, Ł., Dziwiński, P., Red’ko, V.G. (2017). The Concept on Nonlinear Modelling of Dynamic Objects Based on State Transition Algorithm and Genetic Programming. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10246. Springer, Cham. https://doi.org/10.1007/978-3-319-59060-8_20

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  • DOI: https://doi.org/10.1007/978-3-319-59060-8_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59059-2

  • Online ISBN: 978-3-319-59060-8

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