• 한국공간구조학회논문집
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• 제17권2호
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• pp.53-62
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• 2017

This study aims to establish a seismic resistance performance evaluation method that makes sure to secure the seismic resistance performance of the existing mid-low story reinforced concrete structures. This study focuses on the development of the seismic resistance performance evaluation method for the overall seismic resistance performance evaluation on the buildings by applying fuzzy theory. This seismic resistance performance evaluation method considers the mutual relations among the type of force, the type of member, the type of story, and the states of deterioration of the buildings. The total seismic resistance performance index from this method was calculated by the intensity weight of each evaluation item, fuzzy measure, fuzzy integration. Moreover, the evaluation methodology was established in this study to identify the performance level of the Immediate Occupancy, Life Safe, Collapse Prevention by applying the fuzzy theory.

• 지능정보연구
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• 제3권1호
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• pp.69-81
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• 1997

In this paper, first we propose an architecture of fuzzy neural networks with triangular fuzzy weights. The proposed fuzzy neural network can handle fuzzy input vectors. In both cases, outputs from the fuzzy network are fuzzy vectors. The input-output relation of each unit of the fuzzy neural network is defined by the extention principle of Zadeh. Also we define a cost function for the level sets(i. e., $\alpha$-cuts)of fuzzy outputs and fuzzy targets. Then we derive a learning algorithm from the cost function for adjusting three parameters of each triangular fuzzy weight. Finally, we illustrate our a, pp.oach by computer simulation examples.

• 디지털콘텐츠학회 논문지
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• 제4권1호
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• pp.81-90
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• 2003

분산환경을 기반으로 하는 멀티미디어 플랫폼은 분산 자원 관리를 위해 객체 그룹화에 큰 영향을 받는다. 본 논문에서는 분산 멀티미디어 환경에서 멀티미디어 객체 플랫폼을 위한 가중치와 퍼지 필터링을 이용한 객체 관리 플랫폼을 제안한다. 가중치와 퍼지 필터링 기법은 멀티미디어 객체들의 참조적 관계를 결정하기 위해 사용되며, 객체 플랫폼을 위해 객체 사전 구조를 제안한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1218-1221
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• 1993

The elevator group control systems are the control systems that manage systematically three or more elevators in order to efficiently transport the passingers. In the elevator group control system, the area-weight which determines the load biases of elevators is a control parameter closely related to the system performance. This paper proposes a fuzzy model based method to determine the are-weight. The proposed method uses a two-stage fuzzy inference model which is built by the study of area-weight properties and expert knowledge. The proposed method shows the more desirable results than the conventional method in the simulations that use real traffic data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1324-1329
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• 2004

In this article we have tested stability of classifier based on fuzzy similarity in generalized Lukasiewicz structure. Two different tests for stability was made:In on test stability was checked respect to weight parameters and other test was carried out for idealvectors. Tests have made with three different classification problems.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.76-78
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• 1996

When data is classified and each class has weight, the mean of data is a weighted average. When the class values and weights are trapezoidal fuzzy numbers, we can prove the weghted average is a fuzzy number though not trapezoidal. Its 4 corner points are obtained.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.63-68
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• 1998

This paper proposes fuzzy regression analysis with non-symmetric fuzzy coefficients. By assuming non-symmetric triangular fuzzy coefficients and applying the quadratic programming fomulation, the center of the obtained fuzzy regression model attains more central tendency compared to the one with symmetric triangular fuzzy coefficients. For a data set composed of crisp inputs-fuzzy outputs, two approximation models called an upper approximation model and a lower approximation model are considered as the regression models. Thus, we also propose an integrated quadratic programming problem by which the upper approximation model always includes the lower approximation model at any threshold level under the assumption of the same centers in the two approximation models. Sensitivities of Weight coefficients in the proposed quadratic programming approaches are investigated through real data.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권2호
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• pp.48-54
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• 2002

In this study, a neuro-fuzzy controller which has the characteristic of fuzzy control and artificial neural network is designed. A fuzzy rule to be applied is automatically selected by the allocated neurons. The neurons correspond to fuzzy rules are created by an expert. To adapt the more precise model is implemented by error back-propagation learning algorithm to adjust the link-weight of fuzzy membership function in the neuro-fuzzy controller. The more classified fuzzy rule is used to include the property of dual mode method. In order to verify the effectiveness of the proposed algorithm designed above, an operating characteristic of a DC servo motor with variable load is investigated.

• 한국정보처리학회논문지
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• 제3권3호
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• pp.449-459
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• 1996

본 논문의 퍼지 수리 형태학의 새로운 정의와 신경망을 이용한 이의 구현을 소개 함에 주 목적을 두고 있다. 이 새로운 정의에는 generalized-mean연산자가 중요한 역할을 하고 있다. 본 정의는 신경망을 이용한 구현에 매우 적합할. 연결자 공유 (shared-weight) 신경망의 전반부는 수리 형태적 연산을 수행하기에 적합한 구조를 가 지고 있다. 이 연결자 공유 신경망은 퍼지 수리형태학적 연산을 이용하여 추출 된 특성 정보를 근거로 하여 형태 분류를 수행한다. 따라서, 본 퍼지 정의의 파라 미터들은 신경망의 학습기법을 이용하여 최적화를 기할수 있다. 구조소들(structuring gelements), membership의 값, 그리고 가중 요소(weighting factor)들을 결정하기 위한 학습방법 (learning rule)들이 자세히 열거되어 있다. 적용 예로서 필기체 숫자 인식 문제에 응용한 결과, 퍼지수리 형태학을 이용한 신경망은 이 문제에 있어 현존하는 최고의 결과들과 충분히 견줄만한 결과를 보여주고 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.360-363
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• 1993

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of rules from human operator. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.