نتایج جستجو برای: fuzzy co norm

تعداد نتایج: 463878  

2010
Tomasz PRZYBYŁA Dawid ROJ Janusz JEŻEWSKI Adam MATONIA

This paper presents a new hybrid fuzzy clustering method. In the proposed method, cluster prototypes are values that minimize the introduced generalized cost function. The proposed method can be considered as a generalization of fuzzy c-means (FCM) method as well as the fuzzy c-median (FCMed) clustering method. The generalization of the cluster cost function is made by applying the Lp norm. The...

2009
Benjamín R. C. Bedregal Graçaliz Pereira Dimuro Renata Hax Sander Reiser

The aim of this work is to introduce an approach for interval-valued R-implications, which satisfy some analogous properties of R-implications. We show that the best interval representation of an R-implication that is obtained from a left continuous tnorm coincides with the interval-valued R-implication obtained from the best interval representation of such t-norm, whenever this is an inclusion...

Journal: :Math. Log. Q. 2008
Zuzana Haniková Petr Savický

Propositional fuzzy logics given by a combination of a continuous SBL t-norm with finitely many idempotents and of an involutive negation are investigated. A characterization of continuous t-norms which, in combination with different involutive negations, yield either isomorphic algebras or algebras with distinct and incomparable sets of propositional tautologies is presented.

Journal: :Int. J. Math. Mathematical Sciences 2006
Muhammad Akram Jianming Zhan

We introduce the notion of sensible fuzzy ideals of BCK-algebras with respect to a t-conorm and investigate some of their properties. We give the conditions for a sensible fuzzy subalgebra with respect to a t-conorm to be a sensible fuzzy ideal with respect to a t-conorm. Some properties of the direct product and S-product of fuzzy ideals of BCK-algebras with respect to a t-conorm are also disc...

Journal: :Kybernetika 2010
Julija Lebedinska

This paper is a contribution to the theory of generalized aggregation operators (shortly gagops) introduced by Takači in [11]. The term generalized refers to the inputs of an aggregation operator (shortly agop), they are a special type of fuzzy sets. In the sequel we study a method of construction of a gagop by means of an arbitrary continuous t-norm, called T -extension. Another construction m...

1995
Dan Butnariu Erich Peter Klement

Fuzzy logics based on triangular norms and their corresponding conorms are investigated. An aarmative answer to the question whether in such logics a speciic level of satissability of a set of formulas can be characterized by the same level of satissability of its nite subsets is given. Tautologies, contradictions and contingencies with respect to such fuzzy logics are studied, in particular fo...

2007
Carles Noguera Joan Gispert

xiii Acknowledgements / Agräıments xv

2007
Maciej Wygralak

This paper deals with interval-valued fuzzy sets and I-fuzzy sets, Atanassov's intuitionistic fuzzy sets. They are treated in a systematic way as two, formally equivalent, natural extensions of methods of representing incomplete knowledge about sets. We define and investigate triangular norm-based areas of uncertainty of interval-valued fuzzy sets and I-fuzzy sets, and study some properties of ...

2005
Marcelo E. Coniglio Víctor L. Fernández

In this paper a variation of the fibred semantics of D. Gabbay called plain fibring is proposed, with the aim of combining logics given by matrix semantics. It is proved that the plain fibring of matrix logics is also a matrix logic. Moreover, it is proved that any logic obtained by plain fibring is a conservative extension of the original logics. It is also proposed a simpler version of plain ...

ژورنال: اندیشه آماری 2017
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‎In this paper a new weighted fuzzy ridge regression method for a given set of crisp input and triangular fuzzy output values is proposed‎. ‎In this regard‎, ‎ridge estimator of fuzzy parameters is obtained for regression model and its prediction error is calculated by using the weighted fuzzy norm of crisp ridge coefficients‎. . ‎To evaluate the proposed regression model‎, ‎we introduce the fu...

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