• The Korean Journal of Food And Nutrition
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• v.15 no.3
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• pp.228-234
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• 2002

In this paper, we proposed a preparation of Jeung- pyun (Korean fermented steamed rice cake with sour taste and spongy texture) using fuzzy theory. Before this preparation was introduced, it thoroughly analyzed the existing data of Jeung-pyun preparation with sensory evaluation and instrumental measurement. It defined a membership auction of Fuzzy set by analyzed three sorts of data on Jeung-pyun. And it established the Fuzzy model using the quantity of materials as input, such as rice, flour, wheat flour and fermentation time, and the sensory test scores as output, such as grain, softness, sourness, chewiness, overall quality, pH value and volume, respectively. We got the results that the Fuzzy model was accord with the conventional method with sensory evaluation. And the validity of this method is shown through the computer simulation of the test data. Therefore, the proposed method by Fuzzy model will apply to make Jeung-pyun without sensory evaluation. This study will contribute to develop standard preparation for korean foods and expert system of preparation using computer system.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.1-12
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• 2005

In general, other conventional researches propose the fuzzy Petri net-based fuzzy reasoning algorithms based on the exhaustive search algorithms. If it can allow the certainty factors representing in the fuzzy production rules to use as the heuristic information, then it can allow the reasoning of rule-based systems to perform fuzzy reasoning in more effective manner. This paper presents a fuzzy Petri net(FPN) model to represent the fuzzy production rules of a rule-based system. Based on the fuzzy Petri net model, a weighted fuzzy reasoning algorithm is proposed to Perform the fuzzy reasoning automatically, This algorithm is more effective and more intelligent reasoning than other reasoning methods because it can perform fuzzy reasoning using the certainty factors which are provided by domain experts as heuristic information

• Proceedings of the KAIS Fall Conference
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• 2010.05a
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• pp.89-91
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• 2010

본 논문에서는 학습에 임하는 학생과 교수자의 성향을 좀더 객관성 있게 검출, 면학 효과를 증진시키고자, 학습자와 교수자 상호 소통에 필요한 PCSI(Personal Coaching Styles Inventory)검사 모델을, 러프-퍼지 추론 기반에 의하여 평가하는 방법을 제안한다.

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1880-1893
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• 1996

In this paper, we propose the fuzzy traffic control method in ABR service for the effective use of ATM link. This method, a modified version of EPRCA which is one of rate control methods in ABR service, controls the values of the transmission rates of source by using the fuzzy traffic inference based on switch buffer size and buffer variate rate. For this method, we developed a model and algorithm of the fuzzy traffic control method and a fuzzy traffic controller, after studying fuzzy and neural networks which applied to ATM traffic control and EPRCA. For the fuzzy traffic controller, we also designed a membership function, fuzzy control rules and a max-min inferencing method. We conducted a simulation and compared the link utilization of the fuzzy traffic control method with that of the EPRCA method. The results of the simulation indicated that, compared to EPRCA, the fuzzy traffic control method improves the link utilization by 2.3% in a normal distribution model and by 2.7% in the MMPP model of the source.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.7-12
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• 2007

In this paper, we introduce an approach to design multi-fuzzy controllers for the superheat and the low pressure that have an influence on energy efficiency and stabilization of aft conditioning system. Air conditioning system is composed of compressor, condenser several evaporators and several expansion valves. It is quite difficult to control the air conditioning system because the change of the refrigerant condition give an impact on the overall air conditioning system. In order to solve the drawback, we design multi-fuzzy controllers which control simultaneously both three expansion valve and one compressor for the superheat and the low pressure of air conditioning system. The proposed multi fuzzy controllers are given as two kinds of controller types such as a continuous simplified fuzzy inference type and a discrete fuzzy lookup_table type. Here the scaling factors of each fuzzy controller ate efficiently adjusted by veal coding type Genetic Algorithms. The values of performance index of the conventional type are compared with the simulation results of discrete lookup_table type and continuous simplified inference type.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.759-764
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• 2004

본 연구는 Deng(1989)이 제시한 Grey 모형을 이용하여 성진강댐의 월유입량을 예측하였고 그 방법을 제시하였다. Grey 모형은 시계열모형이나 다른 모형에 비해 비교적 적은 수의 자료를 이용하고, 간단할 수식으로 구성되어 있는 장점이 있으나, 적은 수의 자료로 인해 입력자료가 가지는 증감의 경향(trend)으로 오차가 발생하기 쉽다. 그러므로 예측오차를 극복하기 위해서 Fuzzy 시스템을 결합한 Fuzzy-Grey 모형을 구성하였고 Fuzzy 시스템에 필요한 매개변수를 추정하기 위해 최적화기법인 유전자 알고리즘(GA; Genetic Algorithm)을 이용하였다. Grey 모형과 결합된 Fuzzy 시스템은 현재의 입력자료가 가지는 패턴과 가장 유사한 패턴의 과거자료를 이용하여 현재의 입력자료의 예측오차를 추론해내는 기능을 가진다. 오차를 추론하기 위해서 과거 월유입량 자료중 현재 입력 자료와 유사한 패턴을 Grey 상관도를 이용하여 검색하고, 보다 높은 유사성을 가지는 패턴을 선별하고자 노름(norm)을 사용하였고, 유전자 알고리즘의 탐색공간을 제한하였다. 이렇게 구성한 Fuzzy-Grey 모형을 이용하여 전국적인 가뭄년도였던 1992년, 1988년, 2001년에 대해 섬진강댐의 월유입량을 예측하였다. 오차는 1982년, 2001년, 1988년 순으로 비슷한 크기의 오차가 발생하였는데 결과를 분석하여 보면, 급격한 월유입량의 변화가 있었던 경우에 오차가 크게 발생하였으나 가뭄년도에 대해 월유입량의 불확실성이 큼에도 불구하고 비교적 월유입량의 추세를 잘 예측한 것으로 판단된다. 본 연구에서 적용한 Fuzzy-Grey 모형은 적은 수의 자료를 이용하여 예측하고 예측결과를 다시 입력자료로 사용하는 업데이트 방식을 사용하기 때문에 예측결과의 오차가 완전하게 보정되지 않으면 다음 결과에 역시 오차를 주게 되어 오차보정이 상당히 중요하다는 것을 알 수 있었다. 오차를 보다 효과적으로 보정하기 위해서는 퍼지제어에 사용되는 퍼지규칙의 수를 늘리고, 유입량에 직접적인 영향을 주는 강우량과 연계한 2변수의 Fuzzy-Grey 모형을 이용한다면 보다 정확한 유입량 예측이 가능할 것으로 사료된다.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.780-785
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• 1992

We present a multi-sensor fusion method in positioning control of a robot by using fuzzy logic. In general, the vision sensor is used in the gross motion control and the force/torque sensor is used in the fine motion control. We construct a fuzzy logic controller to combine the vision sensor data and the force/torque sensor data. Also, we apply the fuzzy logic controller to the peg-in-hole process. Simulation results uphold the theoretical results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.141-144
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• 1997

This paper presents a method of navigation sign recognition in indoor environments using a fuzzy inference for an autonomous mobile robot. In order to adapt to image deformation of a navigation sign resulted from variations of view-points and distances, a multi-labeled template matching(MLTM) method and a dynamic area search method(DASM) are proposed. The DASM is proposed to detect correct feature points among incorrect feature points. Finally sugeno-style fuzzy inference are adopted for recognizing the navigation sign.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.105-111
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• 2009

Widely used color information recognition methods based on the RGB color model with static fuzzy inference rules have limitations due to the model itself - the detachment of human vision and applicability of limited environment. In this paper, we propose a method that is based on HSI model with new inference process that resembles human vision recognition process. Also, a user can add, delete, update the inference rules in this system. In our method, we design membership intervals with sine, cosine function in H channel and with functions in trigonometric style in S and I channel. The membership degree is computed via interval merging process. Then, the inference rules are applied to the result in order to infer the color information. Our method is proven to be more intuitive and efficient compared with RGB model in experiment.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.25-31
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• 2009

Widely used color information recognition methods based on the RGB color model with static fuzzy inference rules have limitations due to the model itself-the detachment of human vision and applicability of limited environment. In this paper, we propose a method that is based on HSI model with new inference process that resembles human vision recognition process. Also, a user can add, delete, update the inference rules in this system. In our method, we design membership intervals with sine, cosine function in H channel and with functions in trigonometric style in S and I channel. The membership degree is computed via interval merging process. Then, the inference rules are applied to the result in order to infer the color information. Our method is proven to be more intuitive and efficient compared with RGB model in experiment.