• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.67-72
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity models have been recently utilized, which are based on quadratic programming approach giving more diverse spread coefficients than a linear programming one. SVM also uses quadratic programming approach whose another advantage in interval regression analysis is to be able to integrate both the property of central tendency in least squares and the possibilistic property In fuzzy regression. However this is not a computationally expensive way. SVM allows us to perform interval nonlinear regression analysis by constructing an interval linear regression function in a high dimensional feature space. In particular, SVM is a very attractive approach to model nonlinear interval data. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function for interval nonlinear regression model with crisp inputs and interval output. Experimental results are then presented which indicate the performance of this algorithm.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1220-1223
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• 2002

In this paper, numerical robust stability analysis method and its design are presented. L$_2$robust stability of the fuzzy system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linarization control gains is proposed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.100-104
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• 2003

The SVDD(support vector data description) is one of the most well-known one-class support vector learning methods, in which one tries the strategy of utilizing balls defined on the kernel feature space in order to distinguish a set of normal data from all other possible abnormal objects. The major concern of this paper is to consider the problem of modifying the SVDD into the direction of utilizing ellipsoids instead of balls in order to enable better classification performance. After a brief review about the original SVDD method, this paper establishes a new method utilizing ellipsoids in feature space, and presents a solution in the form of SDP(semi-definite programming) which is an optimization problem based on linear matrix inequalities.

• 한국조명전기설비학회지:조명전기설비
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• 제8권1호
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• pp.37-45
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• 1994

본 논문은 전력계통 운용에 관한 합리적인 유효전력 및 무효전력 제어방법을 제시한 논문으로 무효전력 제어에 퍼지 선형계획법을 적용하여 목적함수의 값을 최소화하고 전체 계산시간을 단축시키고 운용의 융통성을 주기 위하여 시도한 논문으로 본 논문의 특징은 다음과 같다. 1) 유효전력 제어는 선로손실을 고려한 전력수급 평형식으로서 B정수를 이용하지 않고 전력 조류 방정식의 쟈코비 행렬의 스파스한 성질을 이용하여 간단히 계산하고 Lagrange함수법을 이용함으로써 계산시간을 단축시키고 기억용량을 대폭 경감시킬 수 있으며 반복계산을 하지 않고 직접 발전기의 최적부하 배분량을 결정할 수 있다. 2) 무효전력 제어시에도 목적함수로서는 총 선로손실을 취하지 않고 발전소의 총 연료비를 취하여 이를 최소화함으로써 보다 합리적인 경제성을 도모하였다. 또 이때 필요한 제어변수에 대한 발전기 출력시 모선전압의 감도행렬의 계산은 조류 방정식의 쟈코비 행렬의 스파스한 성질을 충분히 이용하여 계산시간을 단축시킬 수 있도록 하였다. 3) 특히 무효전력 제어시에는 많은 함수형 부등식 제약조건을 즉 모선전압의 상하한 제약조건을 일정한 값으로 고정하지 않고 어떤 허용 변동폭을 주어 조건을 완화하는 퍼지 선형계획법을 적용하므로써 확정적인 제약을 갖는 일반 선형계획법을 적용할 때보다 유리한 점이 확인되었다.

• 한국지능시스템학회논문지
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• 제13권5호
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• pp.582-589
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• 2003

본 논문에서는 퍼지 피드백 선형화 제어 시스템에 대한 강인 안정성 해석과 제어기 설계에 대해서 말하고 있다. 제어 대상인 비선형 시스템을 모델링 하는데 있어서 Takagi-Sugeno (TS) 퍼지 모델 기법을 이용하였고, 이때 발생할 수 있는 모델 불화실성과 외란에 대해 그것의 최대 최소 범위를 안다고 가정하였다. 모델링을 통해서 얻어진 폐구간 시스템에 대한 안정성 판별은 Diagonal Norm based Linear Differential Inclusions (DNLDI) 구조를 이용하여 $L_2$ 강인 안정성 해석을 하였다. 또한, 퍼지 피드백 선형화 제어 시스템을 안정화 시키는 최대 이득을 얻기 위하여 LMI 최적화 계산법을 기반으로한 수치 해석법을 제시하였다. 제안된 방법의 효과를 확인하기 위해서 강인 안정성 해석 및 제어 설계에 대한 간단한 모의실험을 하였다.

• Industrial Engineering and Management Systems
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• 제13권1호
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• pp.29-42
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• 2014

Extensive research has been conducted on supplier evaluation and selection as a strategic and crucial component of supply chain management in recent years. However, few articles in the previous literature have been dedicated to the use of fuzzy inference systems as an aid in decision-making. Therefore, this essay attempts to demonstrate the application of this method in evaluating suppliers, based on a comprehensive framework of qualitative and quantitative factors besides the effect of gradual coverage distance. The purpose of this study is to investigate the applicability of the numerous measures and metrics in a multi-objective optimization problem of the supply chain network design with the aim of managing the allocation of orders by coordinating the production lines to satisfy customers' demand. This work presents a dynamic non-linear programming model that examines the important aspects of the strategic planning of the manufacturing in supply chain. The effectiveness of the configured network is illustrated using a sample, following which an exact method is used to solve this multi-objective problem and confirm the validity of the model, and finally the results will be discussed and analyzed.

• 대한전기학회논문지
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• 제41권9호
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• pp.984-993
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• 1992

Fuzzy L.P. with Multi-criteria function is adopted in this VAR planning algorithm to accomplish the optimization of comflicting objectives, such as the amount of the VAR installed and power system loss, while keeping the bus voltage profile within an admissible range. Fuzzy L.P. with Multi-criteria function, a powerful tool dealing with the fuzziness of satisfaction levels of the constraints and the goal of objective functions, enables us to search for the solutions which may contribute in VAR planning. This advantage is not provided by traditional standardized L.P. The effectiveness of the proposed algorithm has been verified by the test on the IEEE-30 bus system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.31-34
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• 1991

This paper presents a voltage-reactive power control algorithm considering fuzziness. In this paper, a coordination technique based on fuzzy set theory is applied for system loss-voltage compromises. Here, we introduce membership functions to measure the adaptability of real power loss of transmission line and the deviation of load bus voltage from the constraints. Then the optimization of problem is solved by a linear programming technique considering the fuzzy set theory. The objective is a degree of satisfaction about the fuzzy decision-making function. The effectiveness of this algorithm has been verified by testing on sample systems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.211-213
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• 1992

Fuzzy L. P. with Multi-criteria function is adopted in this VAR allocation algorithm to accomplish the optimization of co-conflicting objectives, such as the amount of the VAR Installed and power system loss, while keeping the bus voltage profile within an admissible range. fuzzy L. P., a powerful tool dealing with the fuzziness of satisfaction levels of the constraints and the goal of objective functions, enables us to search for the solutions which may contribute in VAR planning. This advantage Is not provided by traditional standardized L. P. The effectiveness of the proposed algorithm has been verified by the test on the IEEE-30 bus system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.103-105
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• 1992

The new approach using fuzzy linear programming with fuzzy multi-criterion is proposed for the best generation mix of a power system. A chracteristic feature of the presented approach is that not only cost but also reliability for goal function can be taken into account by using fuzzy multi-criterion and so more realistic solution can be obtained. The effectiveness of the proposed approach is demonstrated by the best generation mix problem of KEPCO-system size model which contains nuclear, coal, LNG, oil and pump-generator hydro plant in multi-years.