• 대한인간공학회지
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• 제23권2호
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• pp.37-54
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• 2004

Fuzzy theory provides an intelligence treatment model for judgement about information when it needs a solution or a decision making about vague problems. Therefore, fuzzy theory is used for appropriate evaluation and decision on obscure information as human's emotion in human factors, In previous study, fuzzy membership function is defined for judgement infOlmation as human's emotion then ultimate results are deducted through fuzzy inference model. This method uses general CWTent through literature review or max, min and average as representative statics value about considering variables. But, this method makes away with nonlinear's or inegular's factors of human sensibility. Accordingly, application of this method leads to considerable loss of information in the ultimate evaluation. For that reason, this method has a limitation in objective evaluation of human factors. So, this study focuses on development of fuzzy membership function, which evaluates human's emotion or feeling accurately and objectively. We used the regression analysis and reasoned a fuzzy membership function about the relation of the variables. Then we verified the adequacy with the reliability through the experiment after this.

• 한국정보처리학회논문지
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• 제4권1호
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• pp.1-10
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• 1997

본 논문에서는 의미적으로 접근되어 애매성이 있으며 구별하기 힘든 자료를 효과 적으로 관리하기 위한 방안의 하나로 퍼지 집합과 라프 집합을 통합한 퍼지-라프 집 합(Fuzzy-Rough Sets:FRS)을 이용, 관계 데이터베이스를 구성하고 구현하였다. 먼저 불완전한 정보를 데이터베이스로 구성, 표현하는 방법에 대하여 일반적 관계 데이터 베이스를 확장시킨 퍼지 데이터베이스와 라프 데이터베이스를 간략히 살펴본다. 그리 고 퍼지 집합과 라프 집합을 통합한 퍼지-라프 집합을 근거로 퍼지-라프(Fuzzy -Rough:FR)관계데이터베이스를 구성한 후, 펜티엄 컴퓨터(166Mhz)상에서 데이터베이 스 관리 시스템인 엑세스(access)와 비쥬얼베이직(visual)을 도구(tool)로 구현하고 분석 하였다. 본 논문에서는 퍼지 집합의 특성과 라프 집합의 특성을 가진 집합을 기 반으로 한 데이터베이스를 구성, 구현함으로서 데이터의 감소를 유도하였다.

• 한국지능시스템학회논문지
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• 제10권4호
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• pp.351-356
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• 2000

정보 검색은 사용자가 필요로 하는 요구에 가장 적합한 정보를 검색할수 있어야 한다. 정보 검색에서 질의어가 문서에 대하여 어느 정도의 유사성을 가지고 존재하는냐를 기준으로 문서를 순서화 할 때, 실제 순서화된 문서들을 보면 질의어와는 다른 문서들이 순서화 되는 경우를 볼 수 있다. 따라서 본 논문에서는 확장 퍼지 개념 네트워크에 근거 문서 검색을 위한 순의 결정 방법을 제안한다. 확장 퍼지 개념 네트워크에는 개념들 사이에 4가지의 퍼지 관계가 있다. 퍼지 양의 조합, 퍼지 음의 조합, 퍼지 일반화, 및 퍼지 세분화등이 있다. 확장 퍼지 개념 네트워크는 관계 행렬과 관련 행렬로 모델화 하여, 유사도 측정을 하였다.

• 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.

• 전기학회논문지
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• 제59권5호
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• pp.981-989
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• 2010

In this study, we introduce a new architecture of fuzzy inference system. In the fuzzy inference system, we use Fuzzy C-Means clustering algorithm to form the premise part of the rules. The membership functions standing in the premise part of fuzzy rules do not assume any explicit functional forms, but for any input the resulting activation levels of such radial basis functions directly depend upon the distance between data points by means of the Fuzzy C-Means clustering. As the consequent part of fuzzy rules of the fuzzy inference system (being the local model representing input output relation in the corresponding sub-space), four types of polynomial are considered, namely constant, linear, quadratic and modified quadratic. This offers a significant level of design flexibility as each rule could come with a different type of the local model in its consequence. Either the Least Square Estimator (LSE) or the weighted Least Square Estimator (WLSE)-based learning is exploited to estimate the coefficients of the consequent polynomial of fuzzy rules. In fuzzy modeling, complexity and interpretability (or simplicity) as well as accuracy of the obtained model are essential design criteria. The performance of the fuzzy inference system is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules(clusters) and the order of polynomial in the consequent part of the rules. Accordingly we can obtain preferred model structure through an adjustment of such parameters of the fuzzy inference system. Moreover the comparative experimental study between WLSE and LSE is analyzed according to the change of the number of clusters(rules) as well as polynomial type. The superiority of the proposed model is illustrated and also demonstrated with the use of Automobile Miles per Gallon(MPG), Boston housing called Machine Learning dataset, and Mackey-glass time series dataset.

• 융합신호처리학회논문지
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• 제6권2호
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• pp.89-94
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• 2005

본 논문에서는 새로운 방법의 Fuzzy PID 제어기를 제안한다. 우선 절대형 디지털 PID 제어기에서 두 가지 문제점이 있다. 첫째는 매 제어 주기마다 많은 데이터의 합을 구해야 하므로 계산시간이 많이 소요되고, 둘째는 이 계산을 위해 이전의 모든 데이터를 보관하고 있어야 되기 때문에 메모리가 많이 필요한 문제점이 있다. 위의 문제점을 개선하기 위해 속도형 디지털 PID 제어기를 사용한다. 제안한 제어기에서는 PID 제어기의 목표 값과 현재 출력 값의 차인 크리스퍼(crisp) 출력 오차를 그대로 사용하지 않고 퍼지추론의 단계는 가지면서 Rule Table은 갖지 않는 특징이 있으며 출력 소속 함수에 두 변수의 관계와 범위에 의해 도식화된 영역에서 삼각형 무게 중심법으로 비퍼지화된 비선형 출력 값을 PID 계수에 인가하는 새로운 Fuzzy PID 제어기를 제안한다.

• Communications for Statistical Applications and Methods
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• 제15권4호
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• pp.517-530
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• 2008

본 논문은 시간의 흐름에 따라 일정한 간격으로 관측된 시계열자료에 대한 통계적인 관계를 추정하기 위하여 삼각퍼지수를 이용한 퍼지시계열모형을 소개한다. 모든 관측치를 포함하는 전체집합을 분할하는 구간을 자료의 빈도수에 따라 결정하고 연속되는 두 시점에서 퍼지수가 일치하는 경우에는 관측된 자료의 차에 대한 정보를 이용하여 제안된 퍼지시계열모형을 추정한다. 예제를 이용하여 제안된 퍼지시계열모형의 정확성을 일반적인 시계열모형과 여러 가지 방법으로 추정된 퍼지시계열모형과 비교한다.

• Journal of Electrical Engineering and Technology
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• 제2권2호
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• pp.178-187
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• 2007

One important issue in power systems is dynamic instability due to loosing balance relation between electrical generation and a varying load demand that justifies the necessity of stabilization. Moreover, Power System Stabilizer (PSS) must have capability of producing appropriate stabilizing signals over a wide range of operating conditions and disturbances. To overcome these drawbacks, this paper proposes a new method for robust design of PSS by using an auto-tuning fuzzy control in combination with Real-Coded Genetic Algorithm (RCGA). This method includes two fuzzy controllers; internal fuzzy controller and supervisor fuzzy controller. The supervisor controller tunes the internal one by on-line applying of nonlinear scaling factors to inputs and outputs. The RCGA-based method is used for off-line training of this supervisor controller. The proposed PSS is tested in three operational conditions; nominal load, heavy load, and in the case of fault occurrence in transmission line. The simulation results are provided to compare the proposed PSS with conventional fuzzy PSS and conventional PSS. By evaluating the simulation results, it is shown that the performance and robustness of proposed PSS in different operating conditions is more acceptable

• 감성과학
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• 제11권1호
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• pp.1-10
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• 2008

본 논문에서는 퍼지이론을 이용하여 색채공간의 사용자가 원하는 분위기에 해당하는 언어 입력에 따라 조화로운 색채공간을 설계해가는 의사결정 보조 시스템을 개발하였다. 개발된 시스템에서 형용사 이미지 스케일의 언어적인 입력이 주어지면 형용사와 색채와의 관계를 퍼지관계로 가정하고 색채공간의 전체적인 분위기에 맞는 색채가 선택되며 퍼지화된 Moon-Spencer등의 색채조화에 관한 지식은 어울리는 조화색 결정의 탐색 영역을 제한하는 역할을 담당하고 이에 따라 조화색이 결정된다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.346-348
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• 2004

In this rarer, we introduce a new Fuzzy Polynomial Neural Networks (FPNNs)-like structure whose neuron is based on the Fuzzy Set-based Fuzzy Inference System (FS-FIS) and is different from that of FPNNs based on the Fuzzy relation-based Fuzzy Inference System (FR-FIS) and discuss the ability of the new FPNNs-like structurenamed Fuzzy Set-based Polynomial Neural Networks (FSPNN). The premise parts of their fuzzy rules are not identical, while the consequent parts of the both Networks (such as FPNN and FSPNN) are identical. This difference results from the angle of a viewpoint of partition of input space of system. In other word, from a point of view of FS-FIS, the input variables are mutually independent under input space of system, while from a viewpoint of FR-FIS they are related each other. In considering the structures of FPNN-like networks such as FPNN and FSPNN, they are almost similar. Therefore they have the same shortcomings as well as the same virtues on structural side. The proposed design procedure for networks' architecture involves the selection of appropriate nodes with specific local characteristics such as the number of input variables, the order of the polynomial that is constant, linear, quadratic, or modified quadratic functions being viewed as the consequent part of fuzzy rules, and a collection of the specific subset of input variables. On the parameter optimization phase, we adopt Information Granulation (IG) based on HCM clustering algorithm and a standard least square method-based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized FSPNN (gFSPNN), the model is experimented with using gas furnace process dataset.