• 제목/요약/키워드: Fuzzy Index

검색결과 328건 처리시간 0.03초

KOSPI 예측을 위한 NEWFM 기반의 특징입력 및 퍼지규칙 추출 (Extracting Input Features and Fuzzy Rules for forecasting KOSPI Stock Index Based on NEWFM)

  • 이상홍;임준식
    • 인터넷정보학회논문지
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    • 제9권1호
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    • pp.129-135
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    • 2008
  • 본 논문은 가중 퍼지소속함수 기반 신경망(Neural Network with Weighted Fuzzy Membership Functions, NEWFM)을 사용하여 생성된 퍼지규칙과 비중복면적 분산 측정법에 의해 추출된 최소의 특징입력을 이용하여, 1일 후의 KOSPI 예측을 하는 방안을 제안하고 있다. NEWFM은 KOSPI의 최근 32일 동안의 CPPn,m(Current Price Position of day n for n-1 to n-m days)을 이용하여 1일 후의 KOSPI 상승과 하락을 예측한다. 특징입력으로써 CPPn,m과 최근 32일간의 CPPn,m을 웨이블릿 변환한 38개의 계수들 중 비중복면적 분산 측정법을 적용하여 추출된 5개의 계수가 사용되었다. 제안된 방법으로 1991년부터 1998년까지의 실험군을 사용한 결과 평균 67.62%의 예측율을 나타내었다.

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유전자 알고리즘과 하중값을 이용한 퍼지 시스템의 최적화 (Optimization of Fuzzy Systems by Means of GA and Weighting Factor)

  • 박병준;오성권;안태천;김현기
    • 대한전기학회논문지:전력기술부문A
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    • 제48권6호
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    • pp.789-799
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    • 1999
  • In this paper, the optimization of fuzzy inference systems is proposed for fuzzy model of nonlinear systems. A fuzzy model needs to be identified and optimized by means of the definite and systematic methods, because a fuzzy model is primarily acquired by expert's experience. The proposed rule-based fuzzy model implements system structure and parameter identification using the HCM(Hard C-mean) clustering method, genetic algorithms and fuzzy inference method. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. in this paper, nonlinear systems are expressed using the identification of structure such as input variables and the division of fuzzy input subspaces, and the identification of parameters of a fuzzy model. To identify premise parameters of fuzzy model, the genetic algorithms is used and the standard least square method with the gaussian elimination method is utilized for the identification of optimum consequence parameters of fuzzy model. Also, the performance index with weighting factor is proposed to achieve a balance between the performance results of fuzzy model produced for the training and testing data set, and it leads to enhance approximation and predictive performance of fuzzy system. Time series data for gas furnace and sewage treatment process are used to evaluate the performance of the proposed model.

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퍼지 균등화와 언어적인 Hedge를 이용한 GA 기반 퍼지 모델링 (GA based Fuzzy Modeling using Fuzzy Equalization and Linguistic Hedge)

  • 김승석;곽근창;유정웅;전명근
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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    • pp.217-220
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    • 2001
  • The fuzzy equalization method does not require the usual learning step for generating fuzzy rules. However it is heavily depend on the given input-output data set. So, we adapt an hierarchical scheme which sequentially optimizes the fuzzy inference system. Here, the parameters of fuzzy membership functions obtained from the fuzzy equalization are optimized by the genetic algorithm, and then they are also modified to increase the performance index using the linguistic hedge. Finally, we applied it to the Rice taste data and got better results than previous ones.

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HCM 클러스터링과 유전자 알고리즘을 이용한 다중 퍼지 모델 동정 (Identification of Multi-Fuzzy Model by means of HCM Clustering and Genetic Algorithms)

  • 박호성;오성권
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.370-370
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    • 2000
  • In this paper, we design a Multi-Fuzzy model by means of HCM clustering and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model, HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy ate identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy mode] and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

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퍼지DEA에 의한 항만의 효율성 및 순위 측정방법: 평균지수변환모형 접근 (A Measurement Way of Seaport Efficiency and Ranking Using Fuzzy DEA: Average Index Transformation Model Approach)

  • 박노경
    • 한국항만경제학회지
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    • 제26권2호
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    • pp.82-98
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    • 2010
  • 본 연구에서는 첫째, 퍼지DEA모형을 해운항만분야에 이용한 국내외 기존연구들을 간략하게 검토하였으며, 둘째, Campos and Gonzalez(1989), 임성묵(2008)의 평균지수변환모형을 이론적으로 소개하였으며, 셋째, 국내 26개항만을 대상으로 2개의 투입요소(접안능력, 하역능력), 2개의 산출요소(화물처리량, 입출항척수)를 이용하여 평균지수변환모형에 의거하여 효율성을 분석하고 해석하였다. 실증분석결과를 요약해 보면 다음과 같다. 첫째, 일반 투입지향 CCR모형에서는 통영, 고현, 옥포, 속초항이 효율적이었으며, 여수항이 90% 후반의 효율성을 보였다. 둘째, 퍼지DEA 평균지수변환모형에서는 고현, 속초항이 가장 효율적이었으며, 옥포, 여수항은 람다값이 커질수록 효율성이 증가되었다. 또한 완도, 여수, 서귀포항은 람다값이 높아질 수록 효율성수치도 높아졌다. 셋째, 일반적인 투입지향 CCR 모형의 효율성 수치와 평균지수변환법에 의한 효율성수치의 평균순위는 거의 일치하였다. 본 논문이 갖는 정책적인 함의는 국내항만의 정책입안담당자들은 투입요소와 산출요소의 값을 정확히 알지 못하고 애매모호한 수준에서 알고 있을 때, 본 논문에서 사용한 퍼지 DEA 평균지수모형을 이용할 필요성이 있다는 점이다.

X-By-Wire 시스템의 센서 결함 허용을 위한 Fuzzy Hybrid Redundancy 개발 (Development of Fuzzy Hybrid Redundancy for Sensor Fault-Tolerant of X-By-Wire System)

  • 김만호;손병점;이경창;이석
    • 제어로봇시스템학회논문지
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    • 제15권3호
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    • pp.337-345
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    • 2009
  • The dependence of numerous systems on electronic devices is causing rapidly increasing concern over fault tolerance because of safety issues of safety critical system. As an example, a vehicle with electronics-controlled system such as x-by-wire systems, which are replacing rigid mechanical components with dynamically configurable electronic elements, should be fault¬tolerant because a devastating failure could arise without warning. Fault-tolerant systems have been studied in detail, mainly in the field of aeronautics. As an alternative to solve these problems, this paper presents the fuzzy hybrid redundancy system that can remove most erroneous faults with fuzzy fault detection algorithm. In addition, several numerical simulation results are given where the fuzzy hybrid redundancy outperforms with general voting method.

Simulation of Fuzzy Reliability Indexes

  • Dong, Yu-Ge;Chen, Xin-Zhao;Cho, Hyun-Deog;Kwon, Jong-Wan
    • Journal of Mechanical Science and Technology
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    • 제17권4호
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    • pp.492-500
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    • 2003
  • By means of the transformation from the problem of fuzzy reliability to the problem of general reliability, a model for analyzing fuzzy reliability is introduced in this paper Because of the complexity of the Problem of the fuzzy reliability, generally speaking, the analytical equations for calculating fuzzy reliability indexes of machine part cannot be obtained in most cases. Therefore, in this paper, an approach is given wherein progressions are employed to calculate them, or a simulation approach is used to estimate them by expressing general reliability indexes as progressions. By utilizing the approach put forwards in the paper, the calculating quantity for analyzing the fuzzy reliability will be reduced : even substantially reduced sometimes. Some examples are taken to explain the feasibility of the model and a simulation approach.

유전자 알고리즘을 이용한 최적의 퍼지제어기 설계방식 (Optimal Fuzzy Controller Design Method using the Genetic Algorithm)

  • 손동설;이용구;엄기환
    • 한국정보통신학회논문지
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    • 제3권2호
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    • pp.363-371
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    • 1999
  • 본 논문에서는 유전자 알고리즘을 이용한 최적의 퍼지 제어기 설계에 대한 방식을 제안한다. 제안하는 방식은 최적화 문제에 매우 효과적인 유전자 알고리즘을 이용하여 퍼지 제어기의 퍼지규칙, 입ㆍ출력 스케일링 펙터를 결정하는 방식이다. 서보 시스템에 적합한 퍼지 규칙은 퍼지 제어기의 성능지표인 적합도 함수를 사용한다. 제안된 제어 방식의 유용성을 확인하기 위하여 단일 링크 매니퓰레이터를 제어 대상으로 시뮬레이션 및 실험을 하여 일반적인 퍼지 제어 방식과 제어 성능 및 특성을 비교 검토한다.

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방사성 폐기물관리에 모호집합론적 접근법의 적용 (Use of Fuzzy Set Theoretical Approach in Radioactive Waste Management)

  • 문주현;김성호
    • 한국에너지공학회:학술대회논문집
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    • 한국에너지공학회 1998년도 추계 학술발표회 논문집
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    • pp.64-68
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    • 1998
  • This paper discusses the potential application of fuzzy set theory to the decision-making in the area of radioactive waste management. the approach proposed in this study is based on the concepts of fuzzy set theory and the hierarchical structure analysis. The linguistic variables and fuzzy numbers are used to aggregate the decision maker's subjective assessments of the decision criteria and of the decision alternatives with respect to these criteria. For each alternative, the fuzzy appropriateness index is evaluated to obtain the final score. Using total integral value method, one of methods for ranking fuzzy numbers, the fuzzy appropriateness indices are ranked. As a case problem, selection of the most suitable option for spent fuel storage is illustrated.

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퍼지 추론 방법을 이용한 퍼지 동정과 유전자 알고리즘에 의한 이의 최적화 (Fuzzy Identification by means of Fuzzy Inference Method and its Optimization by GA)

  • 박병준;박춘성;안태천;오성권
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 B
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    • pp.563-565
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    • 1998
  • In this paper, we are proposed optimization method of fuzzy model in order to complex and nonlinear system. In the fuzzy modeling, a premise identification is very important to describe the charateristics of a given unknown system. Then, the proposed fuzzy model implements system structure and parameter identification, using the fuzzy inference method and genetic algorithms. Inference method for fuzzy model presented in our paper include the simplified inference and linear inference. Time series data for gas furance and sewage treatment process are used to evaluate the performance of the proposed model. Also, the performance index with weighted value is proposed to achieve a balance between the results of performance for the training and testing data.

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