• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.63-71
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• 2011

We present a method to modify the recognition of neural networks by the fuzzy inference in a handwritten digit recognition with large deformations, and we verified the method by the experiment. The neural networks take long time in learning and recognize 100% on the learning pattern. But the neural networks don't show a good recognition on the testing pattern. So, we apply the modified method as the fuzzy inference. As a result, the recognition and false recognition of neural networks was improved 90.2% and 9.8% respectively at 89.6% and 10.4% initially. This approach decreased especially the false recognition on digit 3, 5. We used the density of digit to extract the fuzzy membership function in this experiment. But, because the handwritten digit have varified input patterns, we will get a better recognition by extracting varifed characteristics and applying the composite fuzzy inference. We also propose the application of fuzzy inference on matching the input pattern, than applying strictly the fuzzy inference.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.81-88
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• 2008

In the game balancing. it is so difficult to choose suitable arms among various actions, or arms and to accurately calculate to which level we adjust the balance. The fuzzy method can be properly used in a particular environment which cannot be correctly processed in mathematics or in lessening the time-consuming problems during the accurate number crunching. Because a variety of actions, relations with opponents. previous battle experiences etc. are not easy to be reflected in every occasion, the fuzzy method could be useful in these cases. When the balancing is needed. the data which have been played to that Point are processed by the fuzzy function and calculated to adapt intensity to each action. The ability of characters is regulated in this process. To demonstrate the efficiency of this method. I would like to make clear the excellence of fuzzy method through the following five experiments; a case with invariable ability adjustment, a case adjusted by a randomly chosen action, a case with the strongest weapon selection. a case with the weakest weapon selection and a case with the fuzzy method application.

• Journal of Power Electronics
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• v.5 no.1
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• pp.1-10
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• 2005

This paper presents the application of a simple neuro-based speed control scheme of a permanent magnet (PM) dc motor. To validate its efficiency, the performance characteristics of the proposed simple neuro-based scheme are compared with those of a Neural Network controller and those of a Fuzzy Logic controller under different operating conditions. The comparative results show that the simple neuro-based speed control scheme is robust, accurate and insensitive to load disturbances.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.211-214
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• 2000

The conventional PI controller has been widely used in industrial application due to the simple control algorithm. But it is very difficult to find the optimal PI control gain. Therefore in this paper to obtain optimal performance fuzzy proportional-plus-integral controller for the vector control system of an induction machine is presented. The simulation model is created in MATLAB/SIMULINK. The simulation results demonstrate the good performance of this system.

• Proceedings of the Safety Management and Science Conference
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• 2000.05a
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• pp.207-215
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• 2000

This study deals with the application of knowledge-engineering and a methodology for the assessment & measurement of reliability, availability, maintainability, and safety of industrial systems using fault-tree representation. A fuzzy methodology for fault-tree evaluation seems to be an alternative solution to overcome the drawbacks of the conventional approach(insufficient information concerning the relative frequences of hazard events). To improve the quality of results, the membership functions must be approximated based on heuristic considerations. The purpose of this Is to describe the knowlwdge engineering approach, directed to integrate the various sources of knowledge involved in a FTA.

• Journal of Bio-Environment Control
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• v.4 no.1
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• pp.89-95
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• 1995

퍼지 이론(fuzzy theory)은 정보의 애매성을 다루는 학문으로 과학에 주관성이 도입된 형태의 새로운 학문 분야이다. 인간의 사고를 수치화하고 이를 언어적으로 처리할 수 있는 퍼지 이론은 인공지능(artificial intelligence)의 한 분야로서, 1965년 Lofti Zadeh 교수에 의하여 창안되었다. 초기 기초 연구 중심의 단계에서 현재에는 첨단 전자공학의 발달과 함께 퍼지 제어기의 농업 및 산업 응용이 활발해지고 있으며, 퍼지 칩이나 퍼지 컴퓨터의 개발까지 연구가 진행되고 있다.(중략)

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.496-501
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• 1992

In this paper, the optimal regulating algorithm are developed by adjusting the scaling - factor and estimating the linguistic control rule according to the results which are attaining from the first defined parameters, and the fuzzy level controller is realized usign the algorithm. The proposed controller apply to the fuzzied level control process, the cement grinding plant. The results shows that the control performance is greatly improved.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.857-860
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• 1997

This paper is on the application of fuzzy for fault-type approach using symmetrical components method. To evaluate performance of the proposed technique, we have been tested using a relaying signals obtained from EMTP simulation package.

• Proceedings of the SAREK Conference
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• 2007.06a
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• pp.139-139
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• 2007

• Computational Structural Engineering
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• v.27 no.4
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• pp.68-71
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• 2014

본 학술기사에서는 최근 구조공학에 응용이 활성화되고 있는 퍼지 이론에 대하여 간단히 설명을 하였다. 그리고 퍼지이론의 구조공학 적용 예로, 본 저자가 수행한 퍼지이론을 이용한 원형 CFT의 구속응력 평가 과정을 간략히 소개하였다. 이 예에서도 알 수 있듯이 퍼지이론은 부정확성, 지식의 부족, 애매함에 기인하는 불확실성을 다루는데 있어 적합한 것을 알 수 있으며, 여러 불확성에 인하여 발생하는 오차를 줄이는데 적합한 것으로 판단된다.