• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.13-16
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• 2002

Recently, Szmidt and Kacprzyk[Fuzzy Sets and Systems 118(2001) 467-477] Proposed a non-probabilistic-type entropy measure for intuitionistic fuzzy sets. It is a result of a geometric interpretation of intuitionistic fuzzy sets and uses a ratio of distances between them. They showed that the proposed measure can be defined in terms of the ratio of intuitionistic fuzzy cardinalities: of F∩F$\^$c/ and F∪F$\^$c/, while applying the Hamming distances. In this note, while applying the Euclidean distances, it is also shown that the proposed measure can be defined in terms of the ratio of some function of intuitionistic fuzzy cardinalities: of F∩F$\^$c/ and F∪F$\^$c/.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.250-255
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• 2001

본 논문은 지문 이미지에 존재하는 애매함을 퍼지 로직을 이용한 표현으로 기존의 융선 추적법의 단점을 보완한다. 지문의 근방의 질을 퍼지 집합의 상대 크기와 근방 명암의 분산을 이용하여 판단한 후 근방의 지문의 질이 좋고 나쁨에 즉각적으로 다른 방법을 사용하여 지문의 융선을 추적하는 새로운 융선 추적법을 제안 설계한다.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.65-72
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• 2000

In this paper we propose the new binary image matching algorithm called the Fuzzy logic induced Hausdorff Distance(FHD) for finding the maximally matched image with the query image. The membership histogram is obtained by normalizing the cardinality of the subset with the corresponding radius after obtaining the distribution of the minimum distance computed by the Hausdroff distance between two binary images. in the proposed algorithm, The fuzzy influence method Center of Gravity(COG) is applied to calculate the best matching candidate in the membership function described above. The proposed algorithm shows the excellent results for the face image recognition when the noise is added to the query image as well as for the character recognition.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1998.10a
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• pp.3-8
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• 1998

The present work proposes the potential fuzzy framework, based on fuzzy set theory, for supporting decision-making problems, especially, selection problems of a best design in the area of nuclear energy system. The framework proposed is composed of the hierarchical structure module, the assignment module, the fuzzification module, and the defuzzification module. In the structure module, the relationship among decision objectives, decision criteria, decision sub-criteria, and decision alternatives is hierarchically structured. In the assignment module, linguistic or rank scoring approach can be used to assign subjective and/or vague values to the decision analyst's judgment on decision variables. In the fuzzification module, fuzzy numbers are assigned to these values of decision variables. Using fuzzy arithmetic operations, for each alternative, fuzzy preference index as a fuzzy synthesis measure is obtained. In the defuzzification module, using one of methods ranking fuzzy numbers, these indices are defuzzified to overall utility values as a cardinality measure determining final scores. According these values, alternatives of interest are ranked and an optimal alternative is chosen. To illustrate the applicability of the framework proposed to selection problem, as a case example, the best option choice of four design options under five decision criteria for primary containment wall thickening around large penetrations in an advanced nuclear energy system is studied.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.261-264
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• 2007

퍼지 추론은 애매한 지식을 효과적으로 처리할 수 있는 장점이 있다. 그러나 규칙의 연관속성은 규칙을 과다하게 생성하기 때문에 유용하고 중요한 규칙을 결정하는데 여러 가지 문제점이었다. 본 논문에서는 퍼지 규칙에서 규칙간의 상관성을 고려하여 불필요한 속성을 제거하고, 퍼지규칙의 상대농도를 이용하여 추론결과의 정확성을 유지하면서 규칙의 수를 최소화 하는 방법을 제안한다. 제안한 방법의 타당성을 검증하기 위하여 기존의 규칙 감축 방법에 따른 출론 결과와 비교 검증하였다.