نتایج جستجو برای: fuzzy implication

تعداد نتایج: 124051  

1993
I. Burhan Turksen

The generalization of two-valued (crisp) sets to fuzzy sets gave us a rich and powerful representation scheme within the domain of semantic uncertainty. A parallel generalization of conjunctions and disjunction is needed from tnorms and t-conorms to what we might appropriately call linguistic (fuzzy) connectives, “AND," “OR," etc. In fact a closer look at the canonical forms of the combination ...

2009
Eunjin Kim Ladislav J. Kohout

This paper continues our study in fuzzy interval logic based on the Checklist Paradigm(CP) semantics of Bandler and Kohout. We investigate the fuzzy interval system of negation which was defined by the Sheffer(NAND), the Nicod(NOR) and the implication connectives of m1 interval system in depth. The top-bottom(TOPBOT) pair of fuzzy negation interval shows non-involutive property; however, it sho...

2008
Degang Wang Wenyan Song Hongxing Li

A novel fuzzy reasoning method, called FSI (fuzzy similarity inference) is investigated in this paper. Firstly, the unified forms of FSI which the diverse implication operators can be employed are proposed. And the computational formulas for both fuzzy modus ponens (FMP) and fuzzy modus tollens (FMT) are obtained. Secondly, the unified forms of α-FSI method are established, and the formulas for...

2015
Xiaodong Pan Yang Xu

This paper deals with propositional fuzzy modal logic with evaluated syntax based on MV-algebras. We focus on its semantical theory from the viewpoint of Pavelka’s graded semantics of propositional fuzzy logic, investigate the L-tautologies based on different Kripke frames. We also define the notion of Lsemantical consequence operation, its some basic properties are obtained. Finally, this pape...

2015
Kyoung Ja Lee

Generalizations of (∈, ∈∨ q)-fuzzy filter of R0-algebras is discussed in the paper [Y. B. Jun, S. Z. Song and J. Zhan, Generalizations of (∈, ∈ ∨ q)-fuzzy filters in R0-algebras, Int. J. Math. Math. Sci. Volume 2010, Article ID 918656, 19 pages]. In this paper, further properties of an (∈, ∈ ∨ qk)-fuzzy filter are investigated. Using a class of filters, an (∈, ∈ ∨ qk)-fuzzy filter is constructe...

2017
Wanda Niemyska Michal Baczynski Szymon Wasowicz

A new family of fuzzy implications, motivated by classic Sheffer stroke operator, is introduced. Sheffer stroke, which is a negation of a conjunction and is called NAND as well, is one of the two operators that can be used by itself, without any other logical operators, to constitute a logical formal system. Classical implication can be presented just by Sheffer stroke operator in two ways whic...

2007
Md. Shabiul Islam Mukter Zaman M. S. Bhuyan Masuri Othman

This paper describes the VHDL modeling of temperature controller based on fuzzy logic intended for industrial application. The system is built of four major modules called fuzzification, inference, implication and defuzzification. The composition method selected for the fuzzy model is the Max-Min composition while the Mamdani Min operator was chosen as the implication method. Each module is mod...

2006
Mark Freischlad Martina Schnellenbach-Held Torben Pullmann

In knowledge representation by fuzzy rule based systems two reasoning mechanisms can be distinguished: conjunction-based and implication-based inference. Both approaches have complementary advantages and drawbacks depending on the structure of the knowledge that should be represented. Implicative rule bases are less sensitive to incompleteness of knowledge. However, implication-based inference ...

2003
J. B. KISZKA

In this paper, the upper bounds for a multivariable fuzzy logic controller under G/Sdel's implication are investigated and a generalized multivariable structure of fuzzy controller are proposed. Contribution operators, such as max (v) operation, ensure the greatest upper bound as well as the least upper bound. Conditions which determine an appropriate upper bound are also determined. This theor...

2008
ION IANCU

Using Generalized Modus Ponens reasoning, we examine the values of inferred conclusion when the premise of the rule and the observed fact have a partial overlapping. We work with fuzzy if-then rules with a single input single output and the t-norm t(x, y) = max((1+λ)(x+y−1)−λxy, 0), λ ≥ −1, for composition operation. This t-norm is important to use because for λ = −1 and λ = 0 it gives the very...

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