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Bi-Fuzzy S-Approximation Spaces

Author

Listed:
  • Ronghai Wang

    (School of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
    Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou 362000, China
    Fujian University Laboratory of Intelligent Computing and Information Processing, Quanzhou 362000, China)

  • Xiaojie Xie

    (School of Mathematics and Statistics, Minnan Normal University, Zhangzhou 363000, China)

  • Huilai Zhi

    (School of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou 362000, China
    Fujian Provincial Key Laboratory of Data-Intensive Computing, Quanzhou 362000, China
    Fujian University Laboratory of Intelligent Computing and Information Processing, Quanzhou 362000, China)

Abstract

The S-approximation spaces are significant extension of the rough set model and have been widely applied in intelligent decision-making. However, traditional S-approximation spaces are limited to two crisp universes, whereas bi-fuzzy universes (i.e., two distinct fuzzy domains) are more prevalent in practical applications. To bridge this gap, this study introduces the bi-fuzzy S-approximation spaces (BFS approximation spaces) as an advancement of knowledge space theory’s fuzzy extension. Upper and lower approximation operators are formally defined, and the properties of BFS approximation spaces under various operations, such as complement, intersection and union are systematically explored. Special attention is given to a significant form of these operators, under which the monotonicity and complementary compatibility of BFS approximation spaces are rigorously analyzed. These results not only extend the theoretical framework of S-approximation spaces but also pave the way for further exploration of fuzzy extensions within knowledge space theory.

Suggested Citation

  • Ronghai Wang & Xiaojie Xie & Huilai Zhi, 2025. "Bi-Fuzzy S-Approximation Spaces," Mathematics, MDPI, vol. 13(2), pages 1-19, January.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:2:p:324-:d:1571910
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    References listed on IDEAS

    as
    1. Radwan Abu-Gdairi & Mostafa A. El-Gayar & Mostafa K. El-Bably & Kamel K. Fleifel, 2021. "Two Different Views for Generalized Rough Sets with Applications," Mathematics, MDPI, vol. 9(18), pages 1-21, September.
    2. Pasquale Anselmi & Egidio Robusto & Luca Stefanutti & Debora Chiusole, 2016. "An Upgrading Procedure for Adaptive Assessment of Knowledge," Psychometrika, Springer;The Psychometric Society, vol. 81(2), pages 461-482, June.
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