• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.289-300
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• 2003

In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.

• Honam Mathematical Journal
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• v.27 no.2
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• pp.163-181
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• 2005

We study some properties of intuitionistic fuzzy equivalence relations. Also we introduce the concepts of intuitionistic fuzzy transitive closures and level sets of an intuitionistic fuzzy relation and we investigate some of their properties.

• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.2
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• pp.24-34
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• 1994

Scientific involvement in complex decision-making system, characterized by multicriteria phenomena and fuzziness inherent in the structure of information, requires suitable methods. Especially, when powerful dependent criteria are introduced and their weighted value structure is ignorant, the systems are become more complex. This paper presents a fuzzy dependenced relation model and fuzzy measure model for this kind of multicriteria decision-making. The model we propose is based on fuzzy relation and fuzzy measure in fuzzy systems theory. For the application of the model, a numdrical example is quoted.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.567-572
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• 1991

This paper proposes an algorithm of fuzzy model modification which improves fuzzy relation matrix for multi-input/single output dynamic systems. Zadeh's possibility distribution plays an important role in the proposed algorithm and in the use of fuzzy models which are constructed by the proposed algorithm. The required computer capacity and time for implementing the proposed algorithm and resulting models are significantly reduced by introducing the concept of the referential fuzzy sets. A nonlinear system is given to show that the proposed algorithm can provide the fuzzy model with satisfactory accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.3
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• pp.17-21
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• 1992

In this paper we consider the notion of fuzzy relation as a generalization of that of fuzzy set. For a complete Heyting algebra L. the category set(L) of all L-fuzzy sets is shown to be a bireflective subcategory of the category Rel(L) of all L-fuzzy relations and L-fuzzy relation preserving maps. We investigate categorical structures of subcategories of Rel(L) in view of quasitopos. Among those categories, we include the category L-fuzzy similarity relations with respect to both max-min and max-product compositions, respectively, as a cartesian closed topological category. Moreover, we describe exponential objects explicitly in terms of function space.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.285-297
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• 2004

The general scheme of an algorithm, called an ABS-FRE algorithm, for solving systems of fuzzy relation equations (systems of FRE) via the ABS algorithms is presented. As special cases, two particular algorithms for obtaining the greatest and minimal solutions of systems of FRE are described. Several new operations used in this scheme are given, for instance, operators $\veebar$ and $\underline{\wedge}$ called quasi-inverses of operators $\vee$ and $\wedge$, respectively, etc.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.99-107
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• 2010

This paper is a study about the relationships among topologies and intuitionistic fuzzy topology induced, respectively, by approximation operators and an intuitionistic fuzzy approximation operator associated with an approximation space (X, R), when the relation R on X is precisely reflexive and transitive. In particular, we consider an intuitionistic fuzzy approximation operator on an approximation space X (i.e., a set X with a reflexive and transitive relation on it), which turns out to be an intuitionistic fuzzy closure operator. This intuitionistic fuzzy closure operator gives rise to two saturated fuzzy topologies on X and it turns out that all the level topologies of one of the fuzzy topology coincide and equal to the topology analogously induced on X by a crisp approximation operator. These observations are then applied to intuitionistic fuzzy automata.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.193-196
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• 2008

Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. In this paper, we propose 2. Cao's fuzzy inference method using learning ability witch is used a gradient descent method in order to improve the performances. Because it is difficult to determine the relation matrix elements by trial and error method which is needed many hours and effort. Simulation results are applied linear and nonlinear system show that the proposed inference method has good performances.

• Kyungpook Mathematical Journal
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• v.45 no.1
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• pp.87-87
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• 2005

Using the belongs to relation $({\in})$ and quasi-coincidence with relation (q) between intuitionistic fuzzy points and intuitionistic fuzzy sets, the concept of (${\Phi},\;{\Psi}$)-intuitionistic fuzzy subgroup where ${\Phi},\;{\Psi}$ are any two of {${\in},\;q,\;{\in}{\vee}q,\;{\in}{\wedge}q$} with ${\Phi}\;{\neq}\;{\in}{\wedge}q$ is introduced, and related properties are investigated.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.7-16
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• 2007

First, we investigate fuzzy equivalence relations on a set X in the sense of Youssef and Dib. Second, we discuss fuzzy congruences generated by a given fuzzy relation on a fuzzy groupoid. In particular, we obtain the characterizations of ${\rho}\;o\;{\sigma}{\in}$ FC(S) for any two fuzzy congruences ${\rho}\;and\;{\sigma}$ on a fuzzy groupoid ($S,{\odot}$). Finally, we study the lattice of fuzzy equivalence relations (congruences) on a fuzzy semigroup and give certain lattice theoretic properties.