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Fuzzy implications based on semicopulas
Fuzzy Sets and Systems, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Michal Baczynski 0001 +4 more
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Implicative Fuzzy Associative Memories
IEEE Transactions on Fuzzy Systems, 2006Associative neural memories are models of biological phenomena that allow for the storage of pattern associations and the retrieval of the desired output pattern upon presentation of a possibly noisy or incomplete version of an input pattern. In this paper, we introduce implicative fuzzy associative memories (IFAMs), a class of associative neural ...
Peter Sussner, Marcos Eduardo Valle
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Fuzzy Implications in the Mizar System
2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2021This paper is a description of first steps towards providing the computer-supported formalization of a relatively recent textbook by Baczynski and Jarayam “Fuzzy Implications”. We present some of the issues connected with the use of Mizar-computerized proof assistant together with its extensive repository of mathematical texts checked for their logical
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Fuzzy Implications Generating from Fuzzy Negations
2018A basic building block in the foundation of fuzzy neural networks is the theory of fuzzy implications. Fuzzy implications play a crucial role in this topic. The aim of this paper is to find a new method of generating fuzzy implications. based on a given fuzzy negation.
Georgios Souliotis +1 more
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Fuzzy positive implicative and fuzzy associative filters of lattice implication algebras
Fuzzy Sets and Systems, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Attribute Implications in a Fuzzy Setting
2006The paper is an overview of recent developments concerning attribute implications in a fuzzy setting. Attribute implications are formulas of the form A $\Longrightarrow$ B, where A and B are collections of attributes, which describe dependencies between attributes. Attribute implications are studied in several areas of computer science and mathematics.
Radim Belohlávek, Vilém Vychodil
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On interval fuzzy S-implications
Information Sciences, 2010Let \(\mathbb{U}=\{[a,b] \;| \;0\leq a\leq b\leq 1\}\) denote the set of subintervals of the unit interval. An interval S-implication is a function from \(\mathbb{U}^2\) to \(\mathbb{U}\) based on the functional \(\mathbb{I_{S,N}}(X,Y)=\mathbb{S}(\mathbb{N}(X),Y)\), where \(\mathbb{S}\) is an interval t-conorm and \(\mathbb{N}\) is an interval fuzzy ...
Benjamín R. C. Bedregal +3 more
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On the implication operator in fuzzy logic
Information Sciences, 1983The implication operator in fuzzy logic can be translated into a suitable fuzzy relation in several ways. The problem is which translation/relation to choose. This question has been discussed by several authors so far. In this article various properties of relations, both already known and newly introduced, are thoroughly investigated, e.g.
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Generated fuzzy implicators and fuzzy preference structures
Kybernetika, 2012Following the book by \textit{J. Fodor} and \textit{M. Roubens} [Fuzzy preference modelling and multicriteria decision support. Dordrecht: Kluwer Academic Publishers (1994; Zbl 0827.90002)], a fuzzy preference structure can be constructed by a so-called monotone generator triplet \((p,i,j)\) which has to fulfill some axiomatic properties. In this paper,
Vladislav Biba, Dana Hlinená
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Fuzzy hypotheses for GUHA implications
Fuzzy Sets and Systems, 1998Abstract This paper presents a fuzzy generalization of a sophisticated approach to exploratory data analysis, the general unary hypotheses automaton (GUHA). The GUHA paradigm, to automatically generate sentences of an observational calculus which are supported by given data, has been attracting attention for nearly 30 years.
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