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Associative Probabilistic Neuro-Fuzzy System for Data Classification Under Short Training Set Conditions

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Contemporary Complex Systems and Their Dependability (DepCoS-RELCOMEX 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 761))

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Abstract

The paper proposes a classifying neuro-fuzzy system intended for operating under short training set and nonconvex classes conditions. The proposed system is constructed of feedforward four-layered architecture that solves task of probabilistic classification and fuzzy associative memory which is based on autoassociative evolving memory on fuzzy basis functions that solves fuzzy classification task. An essential aspect of the considered hybrid system of computational intelligence is its high performance and ease of numerical implementation.

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Author information

Authors and Affiliations

  1. Kharkiv National University of Radio Electronics, 14 Nauky av., Kharkiv, 61166, Ukraine

    Yevgeniy Bodyanskiy, Artem Dolotov & Olena Vynokurova

  2. IT Step University, 83a Zamarstynivs’ka str., Lviv, 79019, Ukraine

    Dmytro Peleshko & Olena Vynokurova

  3. Ministry of Education and Science of Ukraine, Kyiv, Ukraine

    Yuriy Rashkevych

Authors
  1. Yevgeniy Bodyanskiy
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  2. Artem Dolotov
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  3. Dmytro Peleshko
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  4. Yuriy Rashkevych
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  5. Olena Vynokurova
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Corresponding author

Correspondence to Yevgeniy Bodyanskiy .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Wojciech Zamojski

  2. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Jacek Mazurkiewicz

  3. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Jarosław Sugier

  4. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Tomasz Walkowiak

  5. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

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Cite this paper

Bodyanskiy, Y., Dolotov, A., Peleshko, D., Rashkevych, Y., Vynokurova, O. (2019). Associative Probabilistic Neuro-Fuzzy System for Data Classification Under Short Training Set Conditions. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds) Contemporary Complex Systems and Their Dependability. DepCoS-RELCOMEX 2018. Advances in Intelligent Systems and Computing, vol 761. Springer, Cham. https://doi.org/10.1007/978-3-319-91446-6_6

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