• 제목/요약/키워드: fuzzy process

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HCM 클러스터링 알고리즘 기반 비퍼지 추론 시스템의 비선형 특성 (Nonlinear Characteristics of Non-Fuzzy Inference Systems Based on HCM Clustering Algorithm)

  • 박건준;이동윤
    • 한국산학기술학회논문지
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    • 제13권11호
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    • pp.5379-5388
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    • 2012
  • 비선형 공정에 대한 퍼지 모델링에서, 퍼지 규칙은 일반적으로 입력 변수 선택, 공간 분할 수 및 소속 함수에 의해 형성된다. 비선형 공정에 대한 퍼지 규칙의 생성은 차원이 증가할수록 규칙의 수가 지수적으로 증가하는 문제를 가지고 있다. 이를 해결하기 위해, 입력 공간의 퍼지 분할에 의한 퍼지 규칙을 생성함으로써 복잡한 비선형 공정을 모델링 할 수 있다. 따라서 본 논문에서는 HCM 클러스터링 알고리즘을 이용하여 입력 공간을 분산 형태로 분할함으로써 비퍼지 추론 시스템의 규칙을 생성한다. 규칙의 전반부 파라미터는 HCM 클러스터링 알고리즘에 의한 소속행렬로 결정된다. 규칙의 후반부는 다항식 함수의 형태로 표현되며, 각 규칙의 후반부 파라미터들은 표준 최소자승법에 의해 동정된다. 마지막으로, 비선형 공정으로는 널리 이용되는 데이터를 이용하여 비선형 특성 및 성능을 평가한다. 본 실험을 통해 고차원의 비선형 시스템은 매우 적은 수의 규칙을 가지고 모델링할 수 있었다.

A Fuzzy-ARTMAP Equalizer for Compensating the Nonlinearity of Satellite Communication Channel

  • Lee, Jung-Sik
    • 한국통신학회논문지
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    • 제26권8B호
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    • pp.1078-1084
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    • 2001
  • In this paper, fuzzy-ARTMAP neural network is applied for compensating the nonlinearity of satellite communication channel. The fuzzy-ARTMAP is made of using fuzzy logic and ART neural network. By a match tracking process with vigilance parameter, fuzzy ARTMAP neural network achieves a minimax learning rule that minimizes predictive error and maximizes generalization. Thus, the system automatically learns a minimal number of recognition categories, or hidden units, to meet accuracy criteria. Simulation studies are performed over satellite nonlinear channels. The performance of proposed fuzzy-ARTMAP equalizer is compared with MLP-basis equalizers.

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누적오차 조정계수를 이용한 위치형 퍼지제어기 (Position-type fuzzy controller using the accumulated error scaling factor)

  • 김동하;전해진;최봉열
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.177-177
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    • 2000
  • In this paper, we propose a two-input two-output fuzzy controller to improve the performance of transient response and to eliminate the steady state error. The outputs of this controller are the control input calculated by position-type fuzzy controller and the accumulated error scaling factor. Here, the accumulated error scaling factor is adjusted on-line by fuzzy rules according to the current trend of the controlled process. To show the usefulness of the proposed controller, it is applied to several systems that are difficult to get satisfactory response by conventional PD controllers or PI controllers.

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비국소 초기 조건을 갖는 비선형 퍼지 미분방정식에 대한 해의 존재성과 유일성 (The existence and uniqueness of solution for the nonlinear fuzzy differential equations with nonlocal initial condition)

  • 박종서;김선유;강점란;권영철
    • 한국지능시스템학회논문지
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    • 제11권8호
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    • pp.715-719
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    • 2001
  • 본 논문에서는 E$^{2}$$_{N}$상에서 비국소 초기 조건을 갖는 비선형 퍼지 미분방정식에 대한 퍼지해의 존재성과 유일성에 관한 연구이다.

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퍼지제어기의 자기동조 방법에 관한 연구 (Self-Tuning Method for Fuzzy Controller)

  • 최한수;김성중
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1993년도 하계학술대회 논문집 A
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    • pp.218-220
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    • 1993
  • This paper deals with a self-tuning fuzzy controller. The fuzzy controller is constructed with linguistic rules which consist of the fuzzy variables and fuzzy sets. Each of fuzzy sets is characterized by a membership function. The tuning fussy controller has paramemters to effect control output. In this paper we propose tuning method for the scaling factor. Computer simulations carried out on a second-order process will show how the present tuning approach improves the transient and steady-state characteristics of the overall system.

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A development of input and output interfaces for fuzzy hierarchical analysis

  • Kwack, H.Y.;Lee, S.D.;Son, I.M.
    • 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.

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Fuzzy Web Usage Mining for User Modeling

  • Jang, Jae-Sung;Jun, Sung-Hae;Oh, Kyung-Whan
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제2권3호
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    • pp.204-209
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    • 2002
  • The interest of data mining in artificial intelligence with fuzzy logic has been increased. Data mining is a process of extracting desirable knowledge and interesting pattern ken large data set. Because of expansion of WWW, web data is more and more huge. Besides mining web contents and web structures, another important task for web mining is web usage mining which mines web log data to discover user access pattern. The goal of web usage mining in this paper is to find interesting user pattern in the web with user feedback. It is very important to find user's characteristic fer e-business environment. In Customer Relationship Management, recommending product and sending e-mail to user by extracted users characteristics are needed. Using our method, we extract user profile from the result of web usage mining. In this research, we concentrate on finding association rules and verify validity of them. The proposed procedure can integrate fuzzy set concept and association rule. Fuzzy association rule uses given server log file and performs several preprocessing tasks. Extracted transaction files are used to find rules by fuzzy web usage mining. To verify the validity of user's feedback, the web log data from our laboratory web server.

간편 간접추론 방식의 퍼지논리에 의한 확장 칼만필터의 성능 향상 (Performance Improvement of an Extended Kalman Filter Using Simplified Indirect Inference Method Fuzzy Logic)

  • 채창현
    • 한국기계가공학회지
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    • 제15권2호
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    • pp.131-138
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    • 2016
  • In order to improve the performance of an extended Kalman filter, a simplified indirect inference method (SIIM) fuzzy logic system (FLS) is proposed. The proposed FLS is composed of two fuzzy input variables, four fuzzy rules and one fuzzy output. Two normalized fuzzy input variables are the variance between the trace of a prior and a posterior covariance matrix, and the residual error of a Kalman algorithm. One fuzzy output variable is the weighting factor to adjust for the Kalman gain. There is no need to decide the number and the membership function of input variables, because we employ the normalized monotone increasing/decreasing function. The single parameter to be determined is the magnitude of a universe of discourse in the output variable. The structure of the proposed FLS is simple and easy to apply to various nonlinear state estimation problems. The simulation results show that the proposed FLS has strong adaptability to estimate the states of the incoming/outgoing moving objects, and outperforms the conventional extended Kalman filter algorithm by providing solutions that are more accurate.

퍼지 적분을 도입한 계증구조 평가 알고리즘 (On the Evaluation Algrithm of Hierarchical Process using $\lambda$-Fuzzy Integral)

  • 여기태;노홍승;이철영
    • 해양환경안전학회지
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    • 제2권1호
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    • pp.97-106
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    • 1996
  • One of the main problems in evaluating complex objects, such as an ill-defined system, is how to treat ambiguous aspect of the evaluation. Due to the Complexity and ambiguity of the objects, many types of evaluation attributes should be identified based on the rational dsision. One of these attributes is an analytical hierarchy process (AHP). the weight of evaluation attribtes in AHP however comes from the probability measure based on the additivity. Therefore, it is notapplicable to the objects which have the property of non-additivity. In the previous studies by other researchers they intriduced the Hierarchical Fuzzy Integral method or mergd AHP and fuzzy measure for the analysis of the overlaps among the evaluation objects. But, they need more anlyses in terms of transformation of the probability measure into fuzzy measure which fits for the additivity and overlapping coefficient which affects to the fuzzy measure. Considering these matters, this paper deals that, ⅰ) clarifying the relation between the fuzzy and probability measure adopted in AHP, ii) calculating directly the family of fuzzy measure from the overlapping coefficient and probability measure. A simple algorithm for the calculation of fuzzy measures and set family of those from the above results is also proposed. Finally, the effectiveness of the algorithm developed by applying this to the problems for estimation of safety in ship berthing and for evaluation of ports in competition is verified. This implied that the new algoritnm gives better description of the system evaluation.

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Fuzzy logic control of robotic deburring process using acoustic emission feedback

  • Choi,Gi Sang;Choi, Gi Heung
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.1687-1692
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    • 1991
  • Burrs, created when metals deform plastically, are by-products of most machining processes. The increasing requirements of precision and reliability in manufacturing processes have led to the development of systems for automated deburring. In this paper the motivations and requirements for automated robotic deburring are discussed. Also, the feasibility of automating the deburring process using fuzzy logic controller is investigated. In implementing the fuzzy logic controller, particular attention is paid to the acoustic emission sensing for the characterization and feedback control of the burr removal process. The results of the experiments reveal the rule based control scheme based on fuzzy logics can be a good alternative to traditional control schemes.

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