• 제목/요약/키워드: Fuzzy measure

검색결과 454건 처리시간 0.023초

Entropy of image fuzzy number by extension principle

  • Hong, Dug-Hun
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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    • pp.5-8
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    • 2002
  • In this paper, we introduce a simple new method on calculating the entropy of the image fuzzy set gotten by the extension principle without calculating its membership function.

퍼지 원 클래스 서포트 벡터 머신 (Fuzzy One Class Support Vector Machine)

  • 김기주;최영식
    • 인터넷정보학회논문지
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    • 제6권3호
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    • pp.159-170
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    • 2005
  • OC-SVM(One Class Support Vector Machine)은 주어진 전체 데이터의 분포를 측정하는 대신에. 데이터 분포의 서포트(support)를 측정하는 기술로서 주어진 데이터를 가장 잘 설명할 수 있는 최적의 서포트 벡터(support vector)를 구하는 기술이다. OC-SVM은 데이터 분포의 표현에 아주 뛰어난 접근 방법이지만, 사람의 주관적인 중요도를 반영하는 것은 힘들다. 본 논문에서는 각 데이터에 퍼지 맴버쉽(fuzzy membership)을 적용하여 기존의 OC-SVM에 사용자의 주관적인 중요도를 표현할 수 있는 FOC-SVM(Fuzzy One class Support Vector Machine)을 유도 하였다. FOC-SVM은 데이터들을 동등하게 다루는 것이 아니라, 데이터 객체의 중요도에 따라 데이터를 다룬다. 즉, 덜 중요한 데이터의 특징 벡터는 OC-SVM의 처리과정에 덜 기여하도록 하기 위하여, 객체의 중요도에 따라 특징 벡터의 크기를 조정하였다. 이를 증명하기 위하여 가상의 데이터를 가지고 실험을 하였고, 실험 결과는 예측된 결과를 보여 주었다.

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Adaptive Fuzzy Inference System using Pruning Techniques

  • Kim, Chang-Hyun;Jang, Byoung-Gi;Lee, Ju-Jang
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.415-418
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    • 2003
  • Fuzzy modelling has the approximation property far the given input-output relationship. Especially, Takagi-Sugeno fuzzy models are widely used because they show very good performance in the nonlinear function approximation problem. But generally there is not the systematic method incorporating the human expert's knowledge or experience in fuzzy rules and it is not easy to End the membership function of fuzzy rule to minimize the output error as well. The ANFIS (Adaptive Network-based Fuzzy Inference Systems) is one of the neural network based fuzzy modelling methods that can be used with various type of fuzzy rules. But in this model, it is the problem to End the optimum number of fuzzy rules in fuzzy model. In this paper, a new fuzzy modelling method based on the ANFIS and pruning techniques with the measure named impact factor is proposed and the performance of proposed method is evaluated with several simulation results.

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그래디언트 감소를 기반으로하는 자기구성 퍼지 제어기의 설계 및 응용 (Design and Application of Gradient-descent-based Self-organizing Fuzzy Logic Controller)

  • 소상호;박동조
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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    • pp.191-196
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    • 1998
  • A new Fuzzy Logic Controller(FLC) called a Gradient-Descent Based Self-Organizing Controller is presented. The Self-Organizing Controller(SOC) has two inputs such as error and change of error, and updates control rules with monitoring a performance measure. There are many works in the SOC which concentrate on the self-organizing ability in control rule base, but have a few research on the performance measure which is akin to sliding mode control. With this procedure, we can get a robust performance measure on the SOC. To verify the perfomance of proposed controller, we have performed for the cart-pole system which is one of the well-known benchmark problem in the control literature.

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퍼지 집합 접근법에 의한 시설배치계획에 관한 연구 (A Study on Layout Planning by a Fuzzy Set Approach)

  • 고창성;김홍배
    • 산업공학
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    • 제6권1호
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    • pp.67-86
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    • 1993
  • This study presents a fuzzy set-theoretic approach for preparing a from-to chart and a relationship chart in order to increase system effectiveness through the proper layout planning. Though there have been a number of studies on the layout planning, they have been not well applied in industries because of difficulties in preparation of the two charts. In this study, a fuzzy mag count as a transportability measure is suggested, and the procedure for preparing two charts is explained on the basis of the count. Finally, this approach is applied to the layout planning of a ship repair shop.

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퍼지 가변 스텝 크기 LMS 알고리즘 (A LMS Algorithm with Fuzzy Variable Step Size)

  • 이철희;김관준
    • 산업기술연구
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    • 제13권
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    • pp.33-41
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    • 1993
  • In this paper, a new LMS algorithm with a fuzzy variable step size (FVS LMS) is presented. The change of step size ${\mu}$, at each iteration which is increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. As a measure of the misadaptation degree, the norm of the cross correlation between the estimation error and input signal is used. Simulation results are presented to compare the performance of the FVSS LMS algorithm with the normalized LMS algorithm.

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A Not on the Value Approximation of Fuzzy Systems Variables

  • Hong, Dug-Hun;Hwang, Seok-Yoon
    • 한국지능시스템학회논문지
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    • 제3권4호
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    • pp.21-23
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    • 1993
  • Under the maxmin compositional rule of inference which is used in applications while executing fuzzy algorithms, Pappis showed that the property of approximation is preserved. In this paper, we generalize a measure of proximity of fuzzy subsets on any set, without the restriction of finiteness. And it is shown that the same property of approximation if preserved under the supmin compositional rule of inference.

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Fuzzy 보호계전기의 기본 설계 (A Preliminary Design of Fuzzy Protective Relay)

  • 이숭재;강상희;김기화;김일동
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.668-670
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    • 1996
  • The conventional relay which determines the fault state based on the current and voltage has a certain limitations due to the uncertainties involved in the data and the decision making criteria. This study proposes the fuzzy relay applying the Belief-Measure to make a decision on the fault based on the various criteria and integrated data.

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Reliability sensitivities with fuzzy random uncertainties using genetic algorithm

  • Jafaria, Parinaz;Jahani, Ehsan
    • Structural Engineering and Mechanics
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    • 제60권3호
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    • pp.413-431
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    • 2016
  • A sensitivity analysis estimates the effect of the change in the uncertain variable parameter on the probability of the structural failure. A novel fuzzy random reliability sensitivity measure of the failure probability is proposed to consider the effect of the epistemic and aleatory uncertainties. The uncertainties of the engineering variables are modeled as fuzzy random variables. Fuzzy quantities are treated using the ${\lambda}$-cut approach. In fact, the fuzzy variables are transformed into the interval variables using the ${\lambda}$-cut approach. Genetic approach considers different possible combinations within the search domain (${\lambda}$-cut) and calculates the parameter sensitivities for each of the combinations.