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A Multidimensional Adaptive Growing Neuro-Fuzzy System and Its Online Learning Procedure

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Advances in Intelligent Systems and Computing II (CSIT 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 689))

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Abstract

The paper presents learning algorithms for a multidimensional adaptive growing neuro-fuzzy system with optimization of a neuron ensemble in every cascade. A building block for this architecture is a multidimensional neo-fuzzy neuron. The demonstrated system is distinguished from the well-recognized cascade systems in its ability to handle multidimensional data sequences in an online fashion, which makes it possible to treat non-stationary stochastic and chaotic data with the demanded accuracy. The most important privilege of the considered hybrid neuro-fuzzy system is its trait to accomplish a procedure of parallel computation for a data stream based on peculiar elements with upgraded approximating properties. The developed system turns out to be rather easy from the effectuation standpoint; it holds a high processing speed and approximating features. Compared to acclaimed countertypes, the developed system guarantees computational simpleness and owns both filtering and tracking aptitudes. The proposed system, which is ultimately a growing (evolving) system of computational intelligence, assures processing the incoming data in an online fashion just unlike the rest of conventional systems.

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Acknowledgment

This research project is partially subvented by RAMECS and CCNU16A02015.

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Authors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, 152 Louyu Road, 430079, Wuhan, China

    Zhengbing Hu

  2. Control Systems Research Laboratory, Kharkiv National University of Radio Electronics, 14 Nauky Ave., 61166, Kharkiv, Ukraine

    Yevgeniy V. Bodyanskiy & Oleksii K. Tyshchenko

Authors
  1. Zhengbing Hu
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  2. Yevgeniy V. Bodyanskiy
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  3. Oleksii K. Tyshchenko
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Corresponding author

Correspondence to Oleksii K. Tyshchenko .

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Editors and Affiliations

  1. Lviv Polytechnic National University, Lviv, Ukraine

    Natalia Shakhovska

  2. IRTC ITS NASU, Kiev, Ukraine

    Volodymyr Stepashko

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Hu, Z., Bodyanskiy, Y.V., Tyshchenko, O.K. (2018). A Multidimensional Adaptive Growing Neuro-Fuzzy System and Its Online Learning Procedure. In: Shakhovska, N., Stepashko, V. (eds) Advances in Intelligent Systems and Computing II. CSIT 2017. Advances in Intelligent Systems and Computing, vol 689. Springer, Cham. https://doi.org/10.1007/978-3-319-70581-1_13

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  • DOI: https://doi.org/10.1007/978-3-319-70581-1_13

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-70581-1

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