• Fire Science and Engineering
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• v.10 no.3
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• pp.19-28
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• 1996

This paper present the way the fire detector determines whether a fire has broken out or not using the fuzzy measure. This method is based on Dempster's combination rule using the belief measure. The detector indicate a 'Fire'(F) or 'Nonfire'(N) when it determines whether a fire has broken out or not. To determine this, the fuzzy rule is applied in the setting value for the heat and smoke detector which is used. As a result, It is proved that the final decision can be determined more exactly whether a fire has broken out or not in proportion to the frequency of the fuzzy measure and the value of Bel (F).

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.11a
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• pp.189-190
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• 2005

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.301-303
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• 1998

This paper presents a new approach to diagnose and detect faults in oil-filled power transformers based on various dissolved gas analyses. A theoretic fuzzy information model is introduced, An inference scheme which yields the 'most' consistent conclusion proposed. A framework is established that allows various dissolved gas analyses to be combined in a systematic way such as the Dempster-Shafer rule. Good diagnosis accuracy is obtained with the proposed approach.

• Korean Journal of Computational Design and Engineering
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• v.5 no.4
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• pp.319-326
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• 2000

Expert systems using uncertain and ambiguous knowledge are not of the recent interests about uncertainty problem for performing inference similar to the decision making of a human expert. Human factors on rule-based systems often involve uncertain information. Expert systems had been used the methods of conflict resolution in a rule conflict situation, but this methods not properly solved the rule conflict. If a human expert appends a new rule to an original rule base, the rule base rightly causes a rule conflict. In this paper, the problem of rule conflict is regarded as one in which uncertainty of information is fundamentally involved. In the reduction of problem with uncertainty, we propose an enhanced rule ordering method, which improve the rule ordering method using Dempster-Shafer theory. We also propose a combinative index, which involve human factors of experts decision making.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1094-1096
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• 1998

An intelligent power transformer protective relaying algorithm based on fuzzy decision-making is proposed. To distinguish external faults with CT saturation, overexcitation and inrush conditions from internal faults, a newly designed fuzzy-rule base is used. The Dempster-Shafer's rule of combition is used for fuzzy inference. A series of the S/W and H/W tests show the proposed protection algorithm has practically sufficient sensitivity and selectivity.

• Journal of Information Technology Application
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• v.1 no.3_4
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• pp.69-90
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• 1999

본 논문은 시계열자료의 ARMA 모형화를 위해 계층적(Hierarchical) 문제해결 방식인 인공신경망 기초 의상결정트리분류기상의 인공신경망 구조를 개선하여 지역문제(Local Problem)를 해결하는 복수개의 인공신경망 결과를 Dempster's rule of combination을 이용하여 종합하는 병행적인 (Parallel) ARMA 모형활르 위한 방법론을 제시함으로써 의사결정트리분류기에 근거한 방법론의 단점을 보완하였다. 본 논문에서 제시한 ARMA 모형화를 위한 방법론은 세 단계로 구성되어 있다: 1) ESACF 특성 벡터 추출단계; 2) 개별 인공신경망에 의한 부분적 모델링 단계; 3) Conflict Resolution 단계, 제시한 방법론을 검증하기 위해 모의실험용 자료와 실제 시계열자료를 이용하여 제시된 방법론을 검증하였으며 실험결과 기존 연구에 비해 ARMA 모형화와 정확도가 높은 것으로 나타났다.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.12
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• pp.1479-1485
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• 1999

This paper proposes a fuzzy decision making method for power transformer protection to identify an internal fault from other transient states such as inrush, over-excitation and an external fault with current transformer (CT) saturation. In this paper, analyzing over 300 EMTP simulations of disturbances, four input variables are selected and fuzzified. At every sampling interval from half to one cycle after a disturbance, from the EMPT simulations, different fuzzy rule base is composed of twelve if-then fuzzy rules associated with their basic probability assignments for singleton- or compound-support hypotheses. Dempster's rule of combination is used to process the fuzzy rules and get the final decision. A series of test results clearly indicate that the method can identify not only an internal fault but also the other transients. The average of relay operation times is about 12(ms). The proposed method is implemented into a Digital Signal Processor (TMS320C31) and tested.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1401-1409
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• 1999

In this paper, a conceptual framework of a new concept of protectability is proposed, which indicates the protection level of the system. Evaluation attributes have been identified and a hierarchical evaluation model has been established. Dempster-Shafer Theory of Evidence is applied in combining multiple uncertain judgements to produce an aggregated evaluation.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1998.10a
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• pp.665-670
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• 1998

본 연구에서는 시계열자료의 ARMA 모형화를 위해 의사결정트리 분류기상에 존재하는 인공신경망의 구조를 개선하여 이들 각각의 인공신경망으로부터 도출된 결과를 Dempster's rule of combination을 이용하여 결합할 수 있는 방법론을 제시하고 있다. 인공신경망을 이용한 기존의 ARMA 모형화 방법과 비교한 결과, 본 연구에서는 제시한 방법이 주어진 ESACF 특성패턴에 대해 보다 정확하게 ARMA 모형화를 하는 것으로 나타났다.

• Journal of Internet Computing and Services
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• v.4 no.1
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• pp.39-52
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• 2003

As software is developed for many applications and software defects have caused serious problem sin those applications, the concern of software quality evaluation increases rapidly. Although there has been many efforts for establishing standards for software evaluation, such as ISO/IEC 9126, they provide only a framework for defining quality characteristics and evaluation process. They, however, do not provide practical guidances for deriving resonable weight value criteria for software evaluation. This paper presents a method to draw quantitative weight values from evaluator's subjective data in the process of software evaluation as observing the ISO/IEC 9126 standard. To eliminate the evaluators' subjectiveness and the uncertainty of weight value during evaluation, the Dempster-Shafer (D-S) theory is adopted and utilized. In this paper, the D-S theory is supplemented with an improved merge rule to reduce the bias of weight value when they are merged with other evaluator's weight value. The proposed merge rule has been tested and proved with actual evaluation data.