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Invariant Fuzzy Implications [PDF]
Soft Computing, 2005 Invariant binary operations on [0,1] are those that remain unchanged under an increasing transformation \(\varphi\) of [0,1], that is, \[ F_\varphi(x,y)=\varphi^{-1}(F(\varphi(x),\varphi(y)) = F(x,y) \] for \(x\) and \(y\) in \([0,1]\). In this paper, the author studies invariant fuzzy implications, and derives that there are exactly 18 such operations,
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A Fuzzy Implication-Based Approach for Validating Climatic Teleconnections
Mathematics, 2022 Fuzzy logic, during recent decades, has evolved into one of the most influential scientific fields. To an extent, this is due to its applications which have a profound impact on the daily life of people worldwide.
Stefanos Makariadis, Basil Papadopoulos
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Generating of fuzzy implications [PDF]
Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology, 2013 This paper deals with some dependencies between fuzzy connectives, on the pattern of laws in a classical propositional calculus, which allow to generate fuzzy implications. Fuzzy implications generated both by a triple: fuzzy conjunction, disjunction and negation, and by two fuzzy implications are considered.
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Fuzzy decision implications: interpretation within fuzzy decision context
CAAI Transactions on Intelligence Technology, 2019 Fuzzy decision implication is an extension of decision implication in the fuzzy setting, serving to uncover the dependencies of fuzzy attributes.
Jing Zhang, Yanhui Zhai, Deyu Li
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Lukasiewicz Fuzzy Implication Operator on Pythagorean Fuzzy Tautological Matrices
, 2021 In this paper, introduced Pythagorean fuzzy tautologial matrices and Pythagorean fuzzy cotautological matrices and some properties of Lukasiwicz implication operator over Pythagorean fuzzy tautologial matrices and Pythagorean fuzzy cotautological ...
Dhanan, Venkatesan
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On Fuzzy Negations Generated by Fuzzy Implications
Formalized Mathematics, 2020 Summary We continue in the Mizar system [2] the formalization of fuzzy implications according to the book of Baczyński and Jayaram “Fuzzy Implications” [1]. In this article we define fuzzy negations and show their connections with previously defined fuzzy implications [4] and [5] and triangular norms and conorms [6].
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SSRN Electronic Journal, 2023 Fuzzy logic (fuzzy sets) possesses some widespread application in decision-making due to its ability to handle uncertainties in the implemented data and information. The application of fuzzy logic in decision-making usually involves the design of fuzzy rule-based systems.
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Pseudo Overlap Functions, Fuzzy Implications and Pseudo Grouping Functions with Applications
Axioms, 2022 Overlap and grouping functions are important aggregation operators, especially in information fusion, classification and decision-making problems. However, when we do more in-depth application research (for example, non-commutative fuzzy reasoning ...
Xiaohong Zhang +6 more
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Complex & Intelligent Systems, 2023 Fuzzy rough set models are useful tools for dealing with fuzzy and real-valued data. They have been used in many real-world applications. In this paper, we investigate the fuzzy rough set model based on triangular norms and fuzzy implications.
Zhaohao Wang
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Generalizations of implication-based fuzzy subalgebras in BCK/BCI-algebras
, 2021 <p>In [2], Jun discussed implication-based subalgebras in BCK/BCI-algebras. In this article, more general forms than Jun's results are discussed. We provide an example to show that a fuzzy subalgebra with thresholds 0 and 0.5 is not an implication ...
G. Muhiuddin and Young Bae Jun
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