COMPARATIVE ANALYSIS OF THE APPLICATION RESULTS OF MAX-MIN CONVOLUTION BASED ON VARIOUS T-NORM AND S-NORM OPERATORS

Authors

  • Bohdan Somriakov Petro Mohyla Black Sea National University
  • Ievgen Sidenko Petro Mohyla Black Sea National University
  • Yuriy Kondratenko Petro Mohyla Black Sea National University

DOI:

https://doi.org/10.34132/mspc2025.01.14.27

Keywords:

Fuzzy logic, min-max convolution, t-norm, s-norm, fuzzy triangular number.

Abstract

This paper presents a comparative analysis of the results of applying max-min convolution based on different t-norm and s-norm operators. The addition of two fuzzy triangular numbers is considered as an example. The authors developed software to compare t-norms and s-norms in max-min convolution using discretization of fuzzy triangular numbers. The results highlight the flexibility of t-norms and s-norms in modeling uncertainty, which makes them valuable for applications in control systems, data analysis, and decision support systems.

References

Zadeh, L.A. (1965) Fuzzy sets. Information and Control, vol. 8, iss. 3, pp. 338-353.

Kondratenko, Y.P., Kondratenko, N.Y. (2018) Synthesis of Analytic Models for Subtraction of Fuzzy Numbers with Various Membership Function’s Shapes. Gil-Lafuente, A., Merigó, J., Dass, B., Verma, R. (eds) Applied Mathematics and Computational Intelligence. FIM 2015. Advances in Intelligent Systems and Computing, vol. 730. Springer, Cham, pp. 87-100.

Piegat, A. (2001) Fuzzy Modeling and Control. Physica Heidelberg.

Published

2025-05-19