• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.239-240
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• 2008

본 논문에서는 Subtractive clustering 알고리즘을 이용한 Fuzzy Radial Basis Function Neural Network (FRBFNN)의 규칙 수를 자동적으로 생성하는 방법을 제시한다. FRBFNN은 멤버쉽 함수로써 기존 RBFNN에서 가우시안이나 타원형 형태의 특정 RBF를 사용하는 구조와 달리 Fuzzy C-Means clustering 알고리즘에서 사용하는 거리에 기한 멤버쉽 함수를 사용하여 전반부의 공간 분할 및 활성화 레벨을 결정하는 구조이다. 본 논문에서는 데이터의 밀집도에 기반을 두어 클러스터링을 하는 Subtractive clustering 알고리즘을 사용하여 퍼지 규칙의 수와 같은 의미를 갖는 분할할 입력공간의 수와 분할된 입력공간의 중심값을 동정하며, Least Square Estimator (LSE) 알고리즘을 사용하여 후반부 다항식의 계수를 추정 한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.20
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• pp.97-104
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• 1989

In this thesis, each objective functions with hierarchical system Bi-level linear programming (BLPP) Problem applications to fuzzy set theory conducted multiple objective programming problem. Using linear fuzzy membership functions make a change typical BLPP and presents modified method turn to account established BLPP method, presents operation results lead to example. Fuzzy Bi-level linear programming problem (FBLPP) can be natural describe realities of life then BLPP.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.457-460
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• 2004

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 PIB 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.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.5
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• pp.553-560
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• 2003

On-site diagnosis of chiller performance is an essential step fur energy saving business. The main purpose of the on-site diagnosis is to predict the COP of a target chiller. Many models based on thermodynamics background have been proposed for this purpose. However, they have to be modified from chiller to chiller and require deep insight into thermodynamics that most of field engineers are often lacking in. This study focuses on developing an easy-to-use diagnostic technique that is based on adaptive neuro-fuzzy inference system (ANFIS). Quality of the training data for ANFIS, sampled over June through September, is assessed by checking COP prediction errors. The architecture of the ANFIS, its error bounds, and collection of training data are described in detail.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.89-95
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• 2001

On-site diagnosis of chiller performance is an essential step for energy saving business. The main purpose of the on-site diagnosis is to predict the COP of a target chiller. Many models based on thermodynamics background have been proposed for the purpose. However, they have to be modified from chiller to chiller and require deep insight into thermodynamics that most of field engineers are often lacking in. This study focuses on developing an easy-to-use diagnostic technique that is based on adaptive neuro-fuzzy inference system (ANFIS). Quality of the training data for ANFIS, sampled over June through September, is assessed by checking COP prediction errors. The architecture of the ANFIS, its error bounds, and collection of training data are described in detail.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.60-65
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• 2000

We propose a new method to deal with the optimal gain self-tuning of the PID controller which is used to industrial process control in various fields. First of all, in this method, first order delay system which was modeled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nickels method. Finally, we can find the parameters of Pm controller so as to maximize the fuzzy inferencl function which includes the maximum overshoot, damping ratio, rising time and settling time. The proposed method also shows good adaptability for variations in characteristics and dead time of the system.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.256-258
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• 2001

전력 계통의 운용 계획을 최적화 하기 위해서 수요예측에 관한 연구가 활발히 진행되고 있다. 기존의 수요예측 기법의 최대 오차는 특수일이 토요일과 월요일인 경우와 연휴인 경우에 발생한다. 이 중 특수일이 토요일과 월요일인 경우는 퍼지 선형회귀분석법과 상대계수법을 이용하여 우수한 결과를 도출한 바 있다. 구정과 추석은 특수일 중 평일과의 부하 차이가 가장 큰 특수일이며 약 $45{\sim}50%$ 정도가 감소된다. 이러한 부하의 감소 폭은 서서히 줄어서 연휴 당일 4일 후에는 완전히 복구가 되며 연휴 전 부하가 낮아지는 시점은 연휴 당일 3일 전이다. 연휴 예측의 불확실성은 연휴 기간의 길이 변동 및 기타 다양한 변수들에 의한 유동성에 기인한다. 특히 추석의 경우 과거 데이터 이용에 더욱 신중해야 하며 타 특수일에 비해 부하 값의 예측이 힘들다. 또한 직전 평일 대비 추석 연휴의 부하는 변화가 심하게 나타나며 본 논문에서는 퍼지 선형회귀분석법을 기본으로 변형된 알고리즘으로 향상된 예측도를 제시한다.

• Journal of Digital Contents Society
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• v.5 no.4
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• pp.311-315
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• 2004

In this paper, we proposed a robust watermarking algorithm based on fuzzy inference and human visual system. In the first, discrete wavelet transform(DWT) is involved to calculate additive energy strength, then we devised fuzzy inference, which was established by computing contrast and texture degree in gray-level image. Watermark is embeded into the coefficients of 3-level DWT so as to consider a spatial effects. Visual recognizable patterns such as binary image were used as a watermark Consequently, experimental results showed that proposed algorithm is robust in JPEC compression.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.353-356
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• 2001

In this paper, we study the existence of fuzzy solution for the following differential system with fuzzy coefficient using the different two methods: (equation omitted), where a, b is the fuzzy natural number generated by fuzzy number l . The a-level set of the fuzzy number (equation omitted). The -level set of a is (equation omitted) and -level set of b is (equation omitted).

• Management & Information Systems Review
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• v.35 no.3
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• pp.173-193
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• 2016

The aim of this paper is to extend the TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) to the fuzzy environment for solving the disaster recovery priority decision problem in credit bureau business information system. In this paper, the rating of each information systems and the weight of each criterion are described by linguistic terms which can be expressed in trapezoidal fuzzy numbers. Then, a vertex method is proposed to calculate the distance between two trapezoidal fuzzy numbers. According to the concept of the TOPSIS, a closeness coefficient is defined to determine the ranking order of all information systems. The combination between the fuzzy set and TOPSIS brings several benefits when compared with other approaches, such that the fuzzy TOPSIS require few fuzzy judgements to parameterization, which contributes to the agility of the decision process, it does not limit the number of alternatives simultaneously evaluated, and it does not cause the ranking reversal problem when a new alternative is included in the evaluation process. This paper is demonstrated with a real case study of a credit rating agency involving 9 evaluation criteria and 9 credit bureau business information systems assessed by 6 evaluators, and provide the systematic disaster recovery framework for BCP(Business Continuity Planning) to practitioner. Finally, this paper show that the procedure of the proposed fuzzy TOPSIS method is well suited as a decision-making tool for the disaster recovery priority decision problem in credit bureau business information system.