• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.246-251
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• 2001

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce system management. Fuzzy theory is very useful method where keywords have vague conditions and system must process that conditions. So, using fuzzy theory, we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.25-29
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• 2005

무선 센서 네트워크에서 센서 노드는 배터리와 같은 제한적인 전원을 가지고 있기 때문에, 센서 노드의 수명을 연장하기 위하여 에너지 효율성을 고려한 다양한 라우팅 프로토콜이 연구되고 있다. 하지만 기존에 제안된 라우팅 프로토콜들은 특정 상황 및 응용에 특화되어 있기 때문에, 하드웨어에 내장시킨 단일 라우팅 프로토콜만으로는 동적으로 변화하는 네트워크 상에서 에너지 효율성을 보장할 수 없다는 문제점이 있다. 본 연구에서는 이러한 문제점을 개선하기 위하여 퍼지 추론 시스템을 기반으로, 다양한 후보 라우팅 프로토콜 중 현재 네트워크 상황에 적합한 라우팅 프로토콜을 선택하여, 이를 동적으로 센서 노드에 적재 혹은 교체하도록 하는 퍼지 기반의 적응형 라우팅 알고리즘을 제안한다. 또한 시뮬레이션을 수행하여 동적인 네트워크 상황 하에서 제안된 라우팅 알고리즘을 사용한 경우가 기존의 단일 라우팅 프로토콜만을 사용한 경우보다 에너지 효율적임을 검증한다.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.255-257
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• 1999

주기억 데이터베이스 시스템은 주기억장치에서 데이터베이스 전체를 상주시킴으로써 빠른 성능을 보장하므로 현재 실시간 데이터베이스 시스템으로 가장 많이 사용되고 있다. 그러나, 시스템에 장애가 발생했을 때는 주기억 데이터베이스의 내용전체가 손실될 수 있다. 그러므로, 주기억 데이터베이스 시스템의 회복 작업은 매우 중요하다. 또한 빠른 회복을 해줄수 있어야 실시간 환경에 적합할 것이다. 빠른 회복을 위한 방법중의 하나는 검사점을 사용하여 회복할 때 분석해야 할 로그의 양을 줄이는 것이다. 본 논문에서는 기존의 검사점 방법들 중 주기억 데이터베이스 환경에 가장 좋은 성능을 보이는 퍼지 검사점에 관한 방법들을 분석 및 보완하여 빠른 회복을 위한 새로운 기법을 제안한다. 구체적으로, 주기억 데이터베이스를 갱신횟수에 따라 파티션을 나눈 후 각 파티션 단위로 퍼지 검사점을 수행할 때 기존 방법은 검사점수행 순서가 비효율적이서 회복시 필요한 로그의 양을 효과적으로 줄일 수 없다. 본 논문에서 제안하는 알고리즘은 파티션별 갱신횟수에 따라 일정한 검사점 수행 간격을 유지하므로 회복시 필요한 로그의 양을 효과적으로 줄임으로써 보다 빠른 회복이 가능하다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.17-18
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• 2008

다변량 퍼지 의사결정트리(이하 MFDT)는 학습 모델의 구조가 간소하고 분류율이 높다는 장점 때문에 일반 퍼지 의사결정트리를 대신해 손동작 인식 시스템의 분류기로 사용되었다. 다양한 사용자의 손동작 특성을 분류하기 위해 여러 개의 인식 모델을 만들고 새로운 사용자에게 가장 적합한 모델을 선택해 사용하는 모델 선택 기법도 손동작 인식에 적용되었다. 모델 선택 과정을 통해 선택된 모델은 기존 모델 중에서 새로운 사용자의 특성에 가장 가깝지만 해당 사용자에 최적화된 모델이라고는 할 수 없다. 이 논문에서는 MFDT 모델을 새로 입력된 데이터를 이용해 적응시키는 방법을 설명하고 실험 결과를 통해 적응 성능을 검증한다.

• Journal of Korea Water Resources Association
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• v.44 no.11
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• pp.903-913
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• 2011

In this paper important factors in determining improvement priorities for water pipes were categorized into the effects of a pipe failure to entire pipe network and the characteristics of individual pipe. Subsequently, mathematical models that can quantify these factors were developed using the Fuzzy techniques. The effects of a pipe failure to entire pipe network and the characteristics of individual pipe that were estimated byFuzzy techniques were coined as Fuzzy Importance Index and Fuzzy Characteristic Index, respectively. The Fuzzy Characteristic Index was further categorized into Fuzzy Deterioration Index and Fuzzy Difficulty Index. Considerations were given to applying weights to specific factors in the developed model depending on the circumstances of model applications. To provide an example of the methodology an example pipe network, Net3, of the EPANET program was used. The Fuzzy Importance Index (FII) and Fuzzy Deterioration Index (FDI) were calculated for the Net3 network by considering the hydraulic effects of a pipe failure on the entire pipe network and the pipe deterioration as one of the individual pipe characteristics. Subsequently, the improvement priorities of the pipes in the Net3 pipe network were established based on the FII and FDI.

• Korean Journal of Cognitive Science
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• v.13 no.1
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• pp.13-21
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• 2002

Fuzzy logic ignores some information in the reasoning process. Neural network is powerful tools for the pattern processing, but, not appropriate for the logical reasoning. To model human knowledge, besides pattern processing capability, the logical reasoning capability is equally important. Another new neural network called neural logic network is able to do the logical reasoning. Because the fuzzy inference is a fuzzy logical reasoning, we construct fuzzy inference network based on the neural logic network, extending the existing rule-inference network. And the traditional propagation rule is modified. Experiments are performed to compare search costs by sequential searching and searching by priority. The experimental results show that the searching by priority is more efficient than the sequential searching as the size of the fuzzy inference network becomes larder and an the number of searching increases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1269-1274
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• 2014

In computer vision research, binarization procedure is one of the most frequently used tools to discriminate target objects from background in grey level binary image. Fuzzy binarization is a reliable technique in environment with high uncertainty such as medical image analysis by setting the threshold as the average of minimum and maximum brightness with triangle type fuzzy membership function. However, this technique is also known as contrast sensitive method thus its discrimination power is not so great when the image has low contrast difference between objects and backgrounds and suffer from information loss as a result. Thus, in this paper, we propose a fuzzy binarization using ART2 algorithm to handle such low contrast image analysis. Proposed ART2 algorithm is applied to determine the medium point of membership function in the fuzzy binarization paradigm. The proposed methods shows low information loss rate in our experiment.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2908-2914
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• 1998

This paper presents an intelligent signal for controling the traffic lights on traffic junction network with dynamic traffic flow, When a junction is connected to adjacent junctions on four sides. Prior researches have been done on the single traffic junction. However, it is dificult to apply single junction controller to real traffic situation. In this paper, we develop a fuzzy taffic network controller which adjusts the extension time of current green phase by using teh fuzzy input variables such as the number of entering cars at the green light, the number of waiting cars during the red light, and the traffic volume. The proposed method was compared to the existing junction signal control methods on controllers in terms of average delay time of cars and the cost function defined in this paper.

• The Transactions of the Korea Information Processing Society
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• v.7 no.9
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• pp.3029-3036
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• 2000

Image segmentation is one of the important processes in the image information extraction for computer vision systems. The fuzzy clustering methods have been extensively used in the image segmentation because it extracts feature information of the region. Most of fuzzy clustering methods have used the Fuzzy C-means(FCM) algorithm. This algorithm can be misclassified about the different size of cluster because the degree of membership depends on highly the distance between data and the centroids of the clusters. This paper proposes a fuzzy clustering algorithm using the Average Intracluster Distance that classifies data uniformly without regard to the size of data sets. The Average Intracluster Distance takes an average of the vector set belong to each cluster and increases in exact proportion to its size and density. The experimental results demonstrate that the proposed approach has the g

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.31-36
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• 2003

The descriptive grade evaluation system is adopting to solve the problems of pre-exiting system that refers to marks and ranks. However, it increases the work load and creates inconsistencies of the grade evaluations due to teachers subjective evaluations. In this Paper, I suggest a grade evaluation system, applying the Fuzzy reasoning on web for teachers to evaluate students more effectively. Teachers can input the results of the accomplishment assessments. It also evaluates with the Fuzzy reasoning to attain the final evaluation of the subjects. The system also creates descriptive evaluation sentences by abstracting some sentences for evaluation utilizing the properties of the Fuzzy reasoning rules.