نتایج جستجو برای: fuzzy compositions and t norms

تعداد نتایج: 16985038  

1999
Vladik Kreinovich

Originally, fuzzy logic was proposed to describe human reasoning. Lately, it turned out that fuzzy logic is also a convenient approximation tool, and that moreover, sometimes a better approximation can be obtained if we use real values outside the interval 0; 1]; it is therefore necessary to describe possible extension of t-norms and t-conorms to such new values. It is reasonable to require tha...

2012
Eduardo S. Palmeira Benjamin R. C. Bedregal

It is proposed in [Extension of Fuzzy Logic Operators Defined on Bounded Lattices via Retractions, Computer & Mathematics with Applications, 63: 1026–1038, 2012] a method for extending t-norms, t-conorms and fuzzy negations from a sublattice M of bounded lattice L considering a relaxed notion of sublattices. In this work we apply this method to extend a class of fuzzy negations constructed from...

1999
Erich Peter Klement Mirko Navara

Among various approaches to fuzzy logics, we have chosen two of them, which are built up in a similar way. Although starting from diierent basic logical connectives, they both use interpretations based on Frank t-norms. Diierent interpretations of the implication lead to diierent axiomatizations, but most logics studied here are complete. We compare the properties, advantages and disadvantages ...

All practical digital circuits are usually a mixture of combinational and sequential logic. Flip–flops are essential to sequential logic therefore fuzzy flip–flops are considered to be among the most essential topics of fuzzy digital circuit. The concept of fuzzy digital circuit is among the most interesting applications of fuzzy sets and logic due to the fact that if there has to be an ultimat...

Journal: :Fuzzy Sets and Systems 2001
Nilesh N. Karnik Jerry M. Mendel

In this paper, we discuss set operations on type-2 fuzzy sets (including join and meet under minimum=product t-norm), algebraic operations, properties of membership grades of type-2 sets, and type-2 relations and their compositions. All this is needed to implement a type-2 fuzzy logic system (FLS). c © 2001 Elsevier Science B.V. All rights reserved.

Journal: :IEEE transactions on neural networks 2003
Leszek Rutkowski Krzysztof Cpalka

In this paper, we derive new neuro-fuzzy structures called flexible neuro-fuzzy inference systems or FLEXNFIS. Based on the input-output data, we learn not only the parameters of the membership functions but also the type of the systems (Mamdani or logical). Moreover, we introduce: 1) softness to fuzzy implication operators, to aggregation of rules and to connectives of antecedents; 2) certaint...

Journal: :Inf. Sci. 2010
Carles Noguera Francesc Esteva Lluis Godo

This paper focuses on the issue of how generalizations of continuous and leftcontinuous t-norms over linearly ordered sets should be from a logical point of view. Taking into account recent results in the scope of algebraic semantics for fuzzy logics over chains with a monoidal residuated operation, we advocate linearly ordered BL-algebras and MTL-algebras as adequate generalizations of continu...

Journal: :FO & DM 2010
Susana Díaz Bernard De Baets Susana Montes

We study the transitivity of fuzzy preference relations, often considered as a fundamental property providing coherence to a decision process. We consider the transitivity of fuzzy relations w.r.t. conjunctors, a general class of binary operations on the unit interval encompassing the class of triangular norms usually considered for this purpose. Having fixed the transitivity of a large prefere...

Journal: :CoRR 2012
Fahimeh Farahbod Mahdi Eftekhari

Fuzzy rule based classification systems are one of the most popular fuzzy modeling systems used in pattern classification problems. This paper investigates the effect of applying nine different T-norms in fuzzy rule based classification systems. In the recent researches, fuzzy versions of confidence and support merits from the field of data mining have been widely used for both rules selecting ...

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