• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 춘계학술대회
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• pp.917-922
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• 2004

As the tasks of robots become more diverse, some complicated tasks have come to require force and position hybrid control. A compliant device can be used to control force and position simultaneously by separating the twist of the robot's end effector from the twist of compliance and freedom by using stiffness mapping of the compliant device. The development of a fuzzy gain scheduling scheme of control for a robot with a compliant device is described in this paper. Fuzzy rules and reasoning are performed on-line to determine the gain of twists based on wrench error and twist error and twist of compliance and twist of freedom ratio. Simulation results demonstrate that better control performance can be achieved in comparison with constant gain control.

• 대한전기학회논문지
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• 제41권8호
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• pp.938-946
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• 1992

A novel 2-dimensional matched filter of the parallel-jaw type using fuzzy logic is proposed for bin picking. Specifically, the averaged pixel intensity of the windowed region for the filtering is considered to be fuzzy. Also membership functions for darkness and brightness are designed by employing the intensity histogram of the image. Then a rule is given to know how much a windowed region can be a possible holdsite. Furthermore eight rules are made to determine the part orientation, where Mamdani's reasoning method is applied. The proposed technique shows better performances than that of the conventional matched filtering technique in the following senses` 1) most of holdsites determined by the proposed technique are not concentrated at the locations nearly the end of part and 2) our filter is rather insensitive to noises than the conventional method. To show the validities of our proposed technique, some experimental results are illustrated and compared with the results by conventional matched filter technique.

• International journal of advanced smart convergence
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• 제12권1호
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• pp.199-207
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• 2023

Trend Impact Analysis is a prominent hybrid method has been used in future studies with a modified surprise- free forecast. It considers experts' perceptions about how future events may change the surprise-free forecast. It is an advanced forecasting tool used in futures studies for identifying, understanding and analyzing the consequences of unprecedented events on future trends. In this paper, we propose an advanced mechanism to generate more justifiable estimates to the probability of occurrence of an unprecedented event as a function of time with different degrees of severity using adaptive neuro-fuzzy inference system (ANFIS). The key idea of the paper is to enhance the generic process of reasoning with fuzzy logic and neural network by adding the additional step of attributes simulation, as unprecedented events do not occur all of a sudden but rather their occurrence is affected by change in the values of a set of attributes. An ANFIS approach is used to identify the occurrence and severity of an event, depending on the values of its trigger attributes.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.532-538
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• 1998

In this paper, a new adaptive fuzzy inference method using neural network based fuzzy reasoning is proposed to make a fuzzy logic control system more adaptive and more effective. In most cases, the design of a fuzzy inference system rely on the method in which an expert or a skilled human operator would operate in that special domain. However, if he has not expert knowledge for any nonlinear environment, it is difficult to control in order to optimize. Thus, using the proposed adaptive structure for the fuzzy reasoning system can controled more adaptive and more effective in nonlinear environment for changing input membership functions and output membership functions. The proposed fuzzy inference algorithm is called adaptive neuro-fuzzy control(ANFC). ANFC can adapt a proper membership function for nonlinear plant, based upon a minimum number of rules and an initial approximate membership function. Nonlinear function approximation and rotary inverted pendulum control system ar employed to demonstrate the viability of the proposed ANFC.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권4호
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• pp.254-259
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• 2008

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

• 전기학회논문지
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• 제63권8호
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• pp.1140-1145
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• 2014

Tunnel lighting is composed of entrance zone, interior zone and exit zone by KS C 3703. We have to consider adaptation at entrance zone and exit zone lighting to prevent deteriorate visibility like black hole and white hole phenomenon. So External luminance, vehicle velocity and traffic volume should be considered in threshold zone lighting and vehicle speed and traffic volume should be considered in interior zone lighting. But existing tunnel lighting system is not good at visibility and economic because that is only controled by external luminance. So in this paper, We improve visibility and economic of tunnel lighting system using fuzzy reasoning according to external luminance, vehicle velocity, traffic volume.

• 지능정보연구
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• 제10권2호
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• pp.91-109
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• 2004

최근 채권의 상환 및 이자의 확실성 정도를 측정하고 연관된 상대적인 위험의 정도를 나타내는 채권등급 평가의 중요성이 대두되고 있다. 초기의 대다수 선행 연구들에서는 기업의 채권 등급예측을 위하여 통계적 기법이 많이 사용되었으나, 많은 연구들에 의해 그 우수성이 보고되고 있는 사례기반 추론 등 인공지능 기법들이 통계모형의 대안으로 제시되어지고 있다. 사례기반 추론에서는 과거의 사례들이 지식으로 표현되고 해결 방법으로 사용된다. 유용한 사례기반 시스템을 구축하기 위해서 시스템의 지식베이스를 구축할 사례들을 인간의 정보처리 과정과 유사한 방법으로 표현하는 것이 중요하다. 본 논문은 실제 세계의 애매모호한 사례들을 다루는데 적절한 퍼지집합개념을 사례기반 추론과 결합하는 통합 방법론을 제시하고자 한다. 퍼지집합이론은 인간이 의사결정시 사용하는 유사한 자연스러운 언어를 수학적으로 변환할 수 있게 해주는 인공지능 기법이다.

• 대한전자공학회논문지TC
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• 제41권10호
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• pp.69-77
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• 2004

본 논문에서는 ATM 망에서의 효율적인 트래픽 제어를 위하여 언어적인 규칙과 퍼지 추론부로 구성되는 퍼지 로직에서 퍼지 규칙을 생성하였다. 퍼지 규칙 내부에 포함된 제어 파라메터들은 주어진 성능 함수를 최소화하도록 학습된다. 즉, 전체 트래픽 도착율과 버퍼의 점유율에 따라 퍼지집합 이론을 통하여 추론한 후 그 비퍼지화값으로 접속된 트래픽에 대해 서버에서의 서비스율을 제어하도록 하였다. 또한, 생성된 퍼지 규칙의 타당성을 검증하기 위하여 MATLAB6.5에서와 온라인 빌드업으로 규칙에 대한 실험결과를 보인다. 그 결과, 전체 트래픽 도착율과 버퍼의 점유율에 따라 효율적으로 서버에서의 서비스율이 제어 됨을 확인하였다.

• Journal of Information Processing Systems
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• 제7권4호
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• pp.595-612
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• 2011

Most organizations use performance appraisal system to evaluate the effectiveness and efficiency of their employees. In evaluating staff performance, performance appraisal usually involves awarding numerical values or linguistic labels to employees performance. These values and labels are used to represent each staff achievement by reasoning incorporated in the arithmetical or statistical methods. However, the staff performance appraisal may involve judgments which are based on imprecise data especially when a person (the superior) tries to interpret another person's (his/her subordinate) performance. Thus, the scores awarded by the appraiser are only approximations. From fuzzy logic perspective, the performance of the appraisee involves the measurement of his/her ability, competence and skills, which are actually fuzzy concepts that can be captured in fuzzy terms. Accordingly, fuzzy approach can be used to handle these imprecision and uncertainty information. Therefore, the performance appraisal system can be examined using Fuzzy Logic Approach, which is carried out in the study. The study utilized a Cascaded fuzzy inference system to generate the performance qualities of some University non-teaching staff that are based on specific performance appraisal criteria.

• 지능정보연구
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• 제10권3호
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• pp.39-57
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• 2004

우유생산 농가에서는 그들 젖소의 우유를 저장하는 탱크 (bulk tank milk: BTM)로부터 채취된 샘플로부터 분석된 우유에 대한 품질관련 항목들, 즉 체세포 수 (somatic cell count: SCC), 표준 plate count (standard plate count: SPC), 사전 incubation count (preliminary incubation count: PIC) 등에 관한 정보를 정기적으로 제공 받는다. 이러한 정보는 일정기간 쌓이게 되면 우유의 품질을 유지하고 목장을 관리할 수 있는 중요한 지식 베이스가 될 수 있다. 그러나 우유 품질이나 목장의 관리상태를 평가하는 기준은 모호하고 퍼지한 용어로 많이 표현되고 있다. 즉 우유 품질을 최상급, 상급, 중간, 불량으로 표시하거나 목장의 관리상태를 아주 양호, 양호, 미흡 등으로 표시한다. 이러한 서술방식은 퍼지이론에서의 모호한 상태를 표현하는 기준과 많이 부합되고 있다. 본 연구의 목적은 BTM으로부터 추출한 샘플로부터 미생물학적 분석을 통해서 나온 결과를 이용해서 BTM의 품질과 목장의 관리상태에 대하여 추론하는 것을 목표로 하고 있다. 따라서 퍼지추론엔진에 기초하여 퍼지로직 기반의 추론방법을 개발하고 실제 데이터를 이용해서 평가하였다. 입력 데이터로는 Bulk Tank SCC, SPC, PIC, laboratory pasteurization count (LPC), non agalactiae Streptococci, Streptococci like organisms, Staphylococcus aureus등이다. 이러한 입력자료에 근거하여 BTM의 품질상태를 아주 양호, 양호, cooling문제, 청결문제, 환경적 mastitis, 환경적/청결 복합문제로 분류하고, 낙농가로부터 채취한 실제 데이터를 이용하여 추론하였다. 본 퍼지 추론 결과는 낙농생산자, 컨설턴트, 수의사 등 관련 종사자들에게 의사결정을 위한 참고자료로서 활용이 가능하다.