Generator of Fuzzy Implications

Author:

Daniilidou Athina1,Konguetsof Avrilia1ORCID,Souliotis Georgios1ORCID,Papadopoulos Basil1ORCID

Affiliation:

1. Department of Civil Engineering, Democritus University of Thrace, 67133 Xanthi, Greece

Abstract

In this research paper, a generator of fuzzy methods based on theorems and axioms of fuzzy logic is derived, analyzed and applied. The family presented generates fuzzy implications according to the value of a selected parameter. The obtained fuzzy implications should satisfy a number of axioms, and the conditions of satisfying the maximum number of axioms are denoted. New theorems are stated and proven based on the rule that the fuzzy function of fuzzy implication, which is strong, leads to fuzzy negation. In this work, the data taken were fuzzified for the application of the new formulae. The fuzzification of the data was undertaken using four kinds of membership degree functions. The new fuzzy functions were compared based on the results obtained after a number of repetitions. The new proposed methodology presents a new family of fuzzy implications, and also an algorithm is shown that produces fuzzy implications so as to be able to select the optimal method of the generator according to the value of a free parameter.

Publisher

MDPI AG

Subject

Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science

Reference50 articles.

1. Fuzzy implication operators and generalized fuzzy method of cases;Ruan;Fuzzy Sets Syst.,1993

2. Makariadis, S., Souliotis, G., and Papadopoulos, B. (2021). Parametric fuzzy implications produced via fuzzy negations with a case study in environmental variables. Symmetry, 13.

3. A method for the detection of the most suitable fuzzy implication for data applications;Iliadis;Communications in Computer and Information Science, Proceedings of the 18th International Conference on Engineering Applications of Neural Networks (EANN), Athens, Greece, 25–27 August 2017,2017

4. A method for the detection of the most suitable fuzzy implication for data applications;Pagouropoulos;Evol. Syst.,2020

5. A method for the evaluation and selection of an appropriate fuzzy implication by using statistical data;Botzoris;Fuzzy Econ. Rev.,2015

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