• 제목/요약/키워드: membership degree

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전문가 시스템의 불확실성 추론 방법

  • 이승재
    • 전기의세계
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    • 제39권8호
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    • pp.7-12
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    • 1990
  • 전문가 시스템에 있어서의 불확실성 정보의 표현 및 처리를 담당하는 주요 추론모델중 Bayesian모델, Certainty Factor 모델 그리고 Dempster-Shafer 모델의 기본이론을 살펴보고자 한다. 이외의 주요 추론 방법으로서 Fuzzy추론 모델이 있는데 이는 판단 지식에 대한 주관적 불확실성과 "매우", "많이" 등의 자연어가 포함하고 있는 불분명성을 체계적이고 효과적으로 다룰 수 있는 Fuzzy Set 이론에 근거한 방법으로서, 불확실성 또는 불명료성을 0에서부터 1 사이의 값을 갖는 membership degree로 표시하며 이를 "MIN"과 "MAX" 함수를 이용한 합성 추론 규칙(Composition Rule of Inference)를 적용하여 처리한다. Fuzzy 추론 모델은 자연어를 포함하는 전문가의 지식 처리에 매우 적합하여 앞으로 그 응용이 높이 기대되는 방법이다. 이외에 Bayesian 모델을 변형 응용한 PROSPECTOR의 Likelyhood Ratio 모델, 정량적 방법인 Theory of Endorsement 모델 등 여러 방법이 있다. 그러나 어느 모델이 더 일반성을 갖고 더 좋은 방법인가 하는 문제에 대하여는 아직 많은 연구가 요구된다. 따라서 이러한 모델들의 전문가 시스템 적용에 있어서는 각 모델의 장단점을 고려하여 주어진 문제 영역에 적합한 모델을 선택하는 것이 바람직하다. 현재 불확실성 처리에 있어서 각 문제에 따른 경험적인 처리에 의존하는 전력 계통 분야의 적용에 있어서도 이러한 실인간 전문가의 추론방법에 근접된 반성을 갖는 불확실성 추론 방버 도입이 요구된다.가의 추론방법에 근접된 반성을 갖는 불확실성 추론 방버 도입이 요구된다.

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Radial Basis Function 네트워크를 이용한 PVC 분류 (Classification of PVC(Premature Ventricular Contraction) using Radial Basis Function network)

  • 이전;이경중
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1997년도 추계학술대회
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    • pp.439-442
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    • 1997
  • In our research, we will extract diagnostic parameters by LPC method and wavelet transform. Then, we will design artificial neural network which is based on RBF that can express input features in terms of fuzzy. Because PVC(Premature Ventricular Contraction) has possibility to cause heart attack, the detection of PVC is a very significant problem. To deal with this problem, LPC method which gives different coefficients or different morphologies and wavelet transform which has superior localization nature of time-frequency, are used to extract effective parameters or classification of normal and PVC. Because RBF network can allocate an input feature to the membership degree of each category, total system will be more flexible.

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퍼지이론을 이용한 호소의 부영양화등급 판정방법 개발 (Development of Fuzzy Method for Judging Lake Eutrophication Grades)

  • 이용운;권병택
    • 환경영향평가
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    • 제15권1호
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    • pp.35-43
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    • 2006
  • The eutrophication in lakes is caused by the inflow of excessive nitrogen and phosphorus, which are not only pollutants to reduce the value of water resource but also nutrients for algae growth that debases water quality. Several methods have been used to judge the eutrophication grades of lakes, but the judgment results can be different with one another even under same coditions because each method is different in judgment items and their standards. A method for overcoming the problem with the judgment of eutrophication grades is, therefore, developed in this study with the application of fuzzy theory. This method allows decision makers to represent the uncertainties (differences) of results by the existing judgment methods and also incorporate associated uncertainties directly into the judgment process, so the judgment results can be made that are more realistic and consistent than those made without taking uncertainty in account.

Intuitionistic Fuzzy Circles

  • Kim, Mi-Hye
    • 한국산학기술학회논문지
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    • 제5권2호
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    • pp.161-165
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    • 2004
  • 본 논문에서는 소속과 비소속의 정도를 나타내는 함수를 쌍으로 가진 intuitionistic 퍼지 원을 소개하고, 그들의 성질을 조사해 보았다. 또한, 퍼지 구의 개념을 2차원 영상에 적용하기 위하여 차원을 제한한 intuitionistic 퍼지 원이 극한 프로세스에 의해 퍼지 기하에 기여함을 볼 수 있다.

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A Robust On-line Signature Verification System

  • Ryu, Sang-Yeun;Lee, Dae-Jong;Chun, Myung-Geun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제3권1호
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    • pp.27-31
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    • 2003
  • This paper proposes a robust on-line signature verification system based on a new segmentation method and fusion scheme. The proposed segmentation method resolves the problem of segment-to-segment comparison where the variation between reference signature and input signature causes the errors in the location and the number of segments. In addition, the fusion scheme is adopted, which discriminates genuineness by calculating each feature vector's fuzzy membership degree yielded from the proposed segmentation method. Experimental results show that the proposed signature verification system has lower False Reject Rate(FRR) for genuine signature and False Accept Rate(FAR) for forgery signature.

On Color Cluster Analysis with Three-dimensional Fuzzy Color Ball

  • Kim, Dae-Won
    • 한국지능시스템학회논문지
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    • 제18권2호
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    • pp.262-267
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    • 2008
  • The focus of this paper is on devising an efficient clustering task for arbitrary color data. In order to tackle this problem, the inherent uncertainty and vagueness of color are represented by a fuzzy color model. By taking a fuzzy approach to color representation, the proposed model makes a soft decision for the vague regions between neighboring colors. A definition on a three-dimensional fuzzy color ball is introduced, and the degree of membership of color is computed by employing a distance measure between a fuzzy color and color data. With the fuzzy color model, a novel fuzzy clustering algorithm for efficient partition of color data is developed.

Fuzzy inference based cover thickness estimation of reinforced concrete structure quantitatively considering salty environment impact

  • Do, Jeong-Yun
    • Computers and Concrete
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    • 제3권2_3호
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    • pp.145-161
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    • 2006
  • This article involves architecting prototype-fuzzy expert system for designing the nominal cover thickness by means of fuzzy inference for quantitatively representing the environment affecting factor to reinforced concrete in chloride-induced corrosion environment. In this work, nominal cover thickness to reinforcement in concrete was determined by the sum of minimum cover thickness and tolerance to that defined from skill level, constructability and the significance of member. Several variables defining the quality of concrete and environment affecting factor (EAF) including relative humidity, temperature, cyclic wet and dry, and the distance from coast were treated as fuzzy variables. To qualify EAF the environment conditions of cycle degree of wet-dry, relative humidity, distance from coast and temperature were used as input variables. To determine the nominal cover thickness a qualified EAF, concrete grade, and watercement ratio were used. The membership functions of each fuzzy variable were generated from the engineering knowledge and intuition based on some references as well as some international codes of practice.

A novel story on rock slope reliability, by an initiative model that incorporated the harmony of damage, probability and fuzziness

  • Wang, Yajun
    • Geomechanics and Engineering
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    • 제12권2호
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    • pp.269-294
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    • 2017
  • This study aimed to realize the creation of fuzzy stochastic damage to describe reliability more essentially with the analysis of harmony of damage conception, probability and fuzzy degree of membership in interval [0,1]. Two kinds of fuzzy behaviors of damage development were deduced. Fuzzy stochastic damage models were established based on the fuzzy memberships functional and equivalent normalization theory. Fuzzy stochastic damage finite element method was developed as the approach to reliability simulation. The three-dimensional fuzzy stochastic damage mechanical behaviors of Jianshan mine slope were analyzed and examined based on this approach. The comprehensive results, including the displacement, stress, damage and their stochastic characteristics, indicate consistently that the failure foci of Jianshan mine slope are the slope-cutting areas where, with the maximal failure probability 40%, the hazardous Domino effects will motivate the neighboring rock bodies' sliding activities.

Nonlinear Function Approximation by Fuzzy-neural Interpolating Networks

  • Suh, Il-Hong;Kim, Tae-Won-
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.1177-1180
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    • 1993
  • In this paper, a fuzzy-neural interpolating network is proposed to efficiently approximate a nonlinear function. Specifically, basis functions are first constructed by Fuzzy Membership Function based Neural Networks (FMFNN). And the fuzzy similarity, which is defined as the degree of matching between actual output value and the output of each basis function, is employed to determine initial weighting of the proposed network. Then the weightings are updated in such a way that square of the error is minimized. To show the capability of function approximation of the proposed fuzzy-neural interpolating network, a numerical example is illustrated.

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Self-Directed Learning Evaluation Using Fuzzy Grade Sheets

  • Kim, Kwang-Baek;Kim, Byung-Joo;Cho, Jae-Hyun
    • Journal of information and communication convergence engineering
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    • 제2권2호
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    • pp.97-101
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    • 2004
  • This paper is about the use of existing evaluation methods, which evaluate learning determined by the score of an exam, which is either a multiple-choice type or single choice type question. These scores don't show the objective evaluations that cause some negative opinions about the scores. In this paper, we propose that the evaluation of the methods of self-directed learning use the triangle-type function of the fuzzy theory so that the learner can objectively evaluate their own learning ability. The proposed method classifies the result of learning into three fuzzy grades to calculate membership, and evaluate the result of an exam according to the final fuzzy grade degree as applied to the fuzzy grade sheets.