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On the Measure of Many-Level Fuzzy Rough Approximation for L-Fuzzy Sets

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Computational Intelligence and Mathematics for Tackling Complex Problems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 819))

Abstract

We introduce a many-level version of L-fuzzy rough approximation operators and define measures of approximation obtained by such operators. In a certain sense, theses measures characterize the quality of the resulting approximation. We study properties of such measures and give a topological interpretation of the obtained results.

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Notes

  1. 1.

    We speak here about a ditopology [1] and not a topology since the degrees of openness and closedness of L-fuzzy sets in our case may be unrelated.

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Acknowledgements

The author is thankful to the referees for reading the paper carefully and making some remarks that allowed to improve the exposition.

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Authors and Affiliations

  1. Institute of Mathematics and CS University of Latvia, Riga, 1459, Latvia

    Alexander Šostak & Ingrida Uljane

  2. Department of Mathematics, University of Latvia, Riga, 1002, Latvia

    Alexander Šostak, Ingrida Uljane & Aleksandrs Elkins

Authors
  1. Alexander Šostak
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  2. Ingrida Uljane
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  3. Aleksandrs Elkins
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Corresponding author

Correspondence to Alexander Šostak .

Editor information

Editors and Affiliations

  1. Faculty of Engineering Sciences, Széchenyi István University, Gyõr, Hungary

    László T Kóczy

  2. Science Faculty, Department of Mathematics, University of Cádiz, Cádiz, Spain

    Jesús Medina-Moreno

  3. Faculty of Economic and Business Sciences, Department of Mathematics, University of Cádiz, Cádiz, Spain

    Eloísa Ramírez-Poussa

  4. Institute of Mathematics and Computer Science, University of Latvia, Riga, Latvia

    Alexander Šostak

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Šostak, A., Uljane, I., Elkins, A. (2020). On the Measure of Many-Level Fuzzy Rough Approximation for L-Fuzzy Sets. In: Kóczy, L., Medina-Moreno, J., Ramírez-Poussa, E., Šostak, A. (eds) Computational Intelligence and Mathematics for Tackling Complex Problems. Studies in Computational Intelligence, vol 819. Springer, Cham. https://doi.org/10.1007/978-3-030-16024-1_23

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