• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1418-1421
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• 1993

The main purpose of this paper is to introduce and develop the notion of a fuzzy measure in separable Banach space. This definition of fuzzy measure is a natural generalization of the set-valued measure. Radon-Nikod m theorems for fuzzy measure are established.

• Journal of applied mathematics & informatics
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• 제41권3호
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• pp.525-540
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• 2023

In this paper, we introduce the concept of fuzzy nano M open and fuzzy nano M closed mappings in fuzzy nano topological spaces. Also, we study about fuzzy nano M Homeomorphism, almost fuzzy nano M totally mappings, almost fuzzy nano M totally continuous mappings and super fuzzy nano M clopen continuous functions and their properties in fuzzy nano topological spaces. By using these mappings, we can able to extended the relation between normal spaces and regular spaces in fuzzy nano topological spaces.

• Journal of applied mathematics & informatics
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• 제42권4호
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• pp.739-748
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• 2024

The intention of this paper is to acquaint domination, total domination on bipolar intuitionistic fuzzy graphs. Subsequently for bipolar intuitionistic fuzzy graphs the domination number and the total domination number are defined. Consequently we proved necessary and sufficient condition for a d-set to be minimal d-set, bounds for domination number and equality conditions for domination number and order.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제19권3호
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• pp.263-271
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• 2012

We introduce the concept of fuzzy $r$-minimal ${\beta}$-open set on a fuzzy minimal space and basic some properties. We also introduce the concept of fuzzy $r-M$ ${\beta}$-continuous mapping which is a generalization of fuzzy $r-M$ continuous mapping and fuzzy $r-M$ semicontinuous mapping, and investigate characterization for the continuity.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.311-313
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• 2001

In this paper, we define type-2 fuzzy mappings on L-L fuzzy numbers and discuss some properties of these mappings.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.95-100
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• 1998

A notion of 'fuzzy' convergence of filters on a set is introduced. We show that the collection of fuzzy L-limit spaces forms a cartesian closed topological category and obtain an interesting relationship between the notions of 'fuzzy' convergence structure and convergence approach spaces.

• 한국지능시스템학회논문지
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• 제27권2호
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• pp.99-105
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• 2017

일반적으로 type-1 fuzzy set 에 존재하는 불확실성을 보다 효율적으로 다루고 제어하기 위하여 Type-2 fuzzy set (T2 FS)이 널리 사용되고 있다. T2 FS에서 퍼지화 상수 (fuzzifier value) m은 이러한 불확실성을 처리하기 위한 가장 중요한 요소이다. 따라서 적절한 퍼지화 상수 값을 결정하는 연구는 여전히 지속되고 있고, 많은 방법들이 연구 되어 왔다. 본 논문에서는 주어진 패턴을 분류하기 위하여 Interval type-2 possibilistic fuzzy C-means (IT2PFCM) 클러스터링 방법을 사용한다. 클러스터링을 위해 사용된 IT2 PFCM 방법에서 각 데이터에 대하여 적응적으로 적절한 퍼지화 상수의 값을 계산하는 방법을 제안한다. 히스토그램 접근법을 통하여 각각의 데이터 포인트로부터 정보를 추출해 내고 추출된 정보를 이용하여 두 개의 퍼지화 상수인 $m_1$, $m_2$. 값을 결정한다. 이렇게 얻어진 값은 interval type-2 fuzzy의 최저 및 최고 멤버쉽 값을 결정하게 된다.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제30권4호
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• pp.429-442
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• 2023

In this paper, we introduce the concept of fuzzy ideals, anti-fuzzy ideals of Γ-BCK-algebras. We study the properties of fuzzy ideals, anti-fuzzy ideals of Γ-BCK-algebras. We prove that if f^-1(µ) is a fuzzy ideal of M, then µ is a fuzzy ideal of N, where f : M → N is an epimorphism of Γ-BCK-algebras M and N.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2305-2307
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• 2000

In this paper we propose a Neuro-Fuzzy modeling method using mGA for complex nonlinear system. mGA has more effective and adaptive structure than sGA with respect to using the changeable-length string. This paper suggest a new coding method for applying the model's input and output data to the number of optimul rules of fuzzy models and the structure and parameter identifications of membership function simultaneously. The proposed method realize optimal fuzzy inference system using the learning ability of Neural network. For fine-tune of the identified parameter by mGA, back-propagation algorithm used for optimulize the parameter of fuzzy set. The proposed fuzzy modeling method is applied to a nonlinear system to prove the superiority of the proposed approach through compare with ANFIS.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.507-509
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• 1999

In this paper, we propose a new fuzzy model identification method that can yield a successful fuzzy rule base for fundamental approximations. The method in this paper uses a set of input-output data and is based on a hybrid messy genetic algorithm (mGA) with a fine-tuning scheme. The mGA processes variable-length strings, while standard GAs work with a fixed-length coding scheme. For successfully identifying a complex nonlinear system, we first use the mGA, which coarsely optimizes the structure and the parameters of the fuzzy inference system, and then the gradient descent method which tine tunes the identified fuzzy model. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its application to a nonlinear approximation.