• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.395-398
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• 2003

Two component analysis methods based on the fuzzy relational calculus are proposed in the setting of the ordered structure. First component analysis is based on a decomposition of fuzzy relation into fuzzy bases, using gradient method. Second one is a component analysis based on the eigen fuzzy sets of fuzzy relation. Through experiments using the test images extracted from SIDBA and View Sphere Database, the effectiveness of the proposed component analysis methods is confirmed. Furthermore, improvements of the image compression/reconstruction and image retrieval based on ordered structure are also indicated.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1996년도 추계학술대회논문집
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• pp.181-184
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• 1996

Fuzzy hierarchical analysis(FHA) has the usefulness to allow decision maker's ambiguities when comparing two alternatives. But, for easiuly appling it to a decision problem, the handling its many data and for decision makers much not knowing fuzzy theory are the obstacles to must be overcomed even if the results of final fuzzy weights can be computed by a personal computer. This paper decribes that FHA is revised, and input/output interfaces are developed to collect input data easily and interprete the fuzzy resultlts. Finally, a fuzzy decision process is suggested with them.

• Journal of Information Processing Systems
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• 제11권2호
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• pp.184-204
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• 2015

Fuzzy Formal Concept Analysis (FCA) is a mathematical tool for the effective representation of imprecise and vague knowledge. However, with a large number of formal concepts from a fuzzy context, the task of knowledge representation becomes complex. Hence, knowledge reduction is an important issue in FCA with a fuzzy setting. The purpose of this current study is to address this issue by proposing a method that computes the corresponding crisp order for the fuzzy relation in a given fuzzy formal context. The obtained formal context using the proposed method provides a fewer number of concepts when compared to original fuzzy context. The resultant lattice structure is a reduced form of its corresponding fuzzy concept lattice and preserves the specialized and generalized concepts, as well as stability. This study also shows a step-by-step demonstration of the proposed method and its application.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.29-33
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• 2001

We propose fuzzy least-squares regression analysis by few error term data and test the slop by fuzzy hypotheses membership function for fuzzy number data with agreement index. Finding the agreement index by area for fuzzy hypotheses membership function and membership function of confidence interval, we obtain the results to acceptance or reject for the test of fuzzy hypotheses.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.36-39
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• 2003

This paper proposes a simultaneous application of homogeneity analysis and fuzzy clustering with in complete data. Taking the similarity between the loss of homogeneity in homogeneity analysis and the least squares criterion in principal component analysis into account, the new objective function is defined in a similar formulation to the linear fuzzy clustering with missing values. Numerical experiment shows the characteristic properties of the proposed method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1090-1093
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• 1993

In this paper, the design technique of fuzzy controller using pole placement method and the stability analysis of the system are discussed. The consequent parts of the fuzzy model representing the fuzzy control system are descrived by linear stated equations. It cannot be guaranteed that the total fuzzy system is stable even if all subsystems are stable. The range of the consequent parameters of fuzzy feedback controller which is stable for each fuzzy subspace of the input space are derived, using a rather simplified stability criterion. Then, the consequent parameters of fuzzy controller is determined with the sufficient condition that the fuzzy feedback controller maintain robust stability for the model of other subspace.

• 자원환경지질
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• 제50권3호
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• pp.239-250
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• 2017

정량적인 산사태 취약성 분석 중 물리 모델 기반의 분석(physically based approach)은 산사태의 발생 메커니즘 과정을 고려할 수 있는 장점으로 인해 다양한 취약성 분석기법 중 가장 효과적인 기법으로 알려져 있다. 물리 모델 분석은 사면의 지형학적 및 지질공학적 특성과 관련된 입력 자료들을 활용하는데, 현장으로부터 지질공학적 특성을 획득하는 과정에서 지반의 공간적 변동성과 복잡한 지질조건으로 인해 불확실성이 발생하며 이는 부정확한 결과를 초래한다. 따라서 이러한 불확실성을 정량화하기 위하여 확률론적 기법이 활용되어 왔다. 그러나 확률론적 분석을 수행하기 위해 필요한 입력변수의 확률특성은 현장 조사나 실험에서의 수량 제약으로 인하여 정확하게 파악하기 힘들다는 문제가 발생한다. 따라서 본 연구에서는 이러한 원인으로 인해 발생하는 불확실성을 다루기 위하여 퍼지집합이론(fuzzy set theory)을 활용하였다. 특히, 본 연구에서는 퍼지집합이론과 몬테카를로기법(Monte Carlo simulation)을 결합한 분석기법을 제안하였고 이를 실제 산사태가 발생한 연구지역에 적용하여 적정성을 파악하였다. 이를 위하여 1998년 8월 대규모의 산사태가 발생한 경상북도 상주시 일대를 연구지역으로 선정하고 산사태 취약성 분석을 수행하였다. 또한 퍼지몬테카를로기법(Fuzzy Monte Carlo simulation)의 예측 정확도 비교를 위해, 기존의 확률론적 기법인 몬테카를로기법(Monte Carlo simulation)과 안전율 수행 결과와 비교분석 하였다. 그 결과 퍼지몬테카를로기법(Fuzzy Monte Carlo simulation)이 다른 기법에 비해 가장 좋은 예측의 정확도를 보였다.

• Journal of applied mathematics & informatics
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• 제8권1호
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• pp.213-223
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• 2001

The use of fuzzy number over interval of confidence instead of possibilitic consideration for solving fuzzy equation is proposed. This approach of solving fuzzy equation by interval arithmetic and ${\alpha}$-cuts has a considerable advantage. Through theoretical analysis, an illustrative example and computational results, we show that the proposed approach is more general and straight-forword.

• Communications for Statistical Applications and Methods
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• 제8권2호
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• pp.319-325
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• 2001

In this note, we propose a simple fuzzy linear regression model for fuzzy input-output data based on Tanaka's approach. Then an LP-based method to derived the satisfying solution of the decision making is developed.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제4권1호
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• pp.39-48
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• 2000

In this paper we define T-fuzzy integrals of set-valued mappings, which are extensions of fuzzy integrals of the single-valued functions defined by Sugeno. And we discuss their properties.