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Fuzzy Models in the Tasks of Pattern Recognition

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Optimization Methods and Applications

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 130))

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Abstract

In this chapter, the approaches to the solution of various problems of artificial intelligence methods are proposed. All methods base on the ideas of inductive mathematics. To investigate the reliability of these methods the elements of the theory of probability of fuzzy events are used.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Rzeszow, Rzeszow, Poland

    Oleksandr I. Provotar

Authors
  1. Oleksandr I. Provotar
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Corresponding author

Correspondence to Oleksandr I. Provotar .

Editor information

Editors and Affiliations

  1. Industrial & Systems Engineering, Texas A&M University, College Station, Texas, USA

    Sergiy Butenko

  2. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  3. Methods of Discrete Optimization, V.M. Glushkov Institute of Cybernetics, Kyiv, Ukraine

    Volodymyr Shylo

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Provotar, O.I. (2017). Fuzzy Models in the Tasks of Pattern Recognition. In: Butenko, S., Pardalos, P., Shylo, V. (eds) Optimization Methods and Applications . Springer Optimization and Its Applications, vol 130. Springer, Cham. https://doi.org/10.1007/978-3-319-68640-0_19

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