• 통상정보연구
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• 제9권1호
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• pp.3-21
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• 2007

The explosive growth of e-marketplace transactions requires an appropriate trust measuring framework to protect involving transacting entities such as buyers and sellers. As a strategic competitive edge, e-marketplace service providers have been adopting various system features that make sure no one transacting entity takes a major risk in online transactions involved. In this paper, an improved trust measuring method using fuzzy theory for an e-marketplace is proposed. The proposed methodology incorporates fuzzy set and calculation concepts to help build trust matrices and models, which are used to measure the level of risk involved in a specific e-marketplace transaction concerned. The proposed framework can be utilized to optimize the transaction costs by recommending a differentiated transaction process according to the risk level involved in each online transaction.

• 대한전기학회논문지:전력기술부문A
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• 제48권6호
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• pp.665-670
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• 1999

This paper introduces a fuzzy expert systems for fault diagnosis, where the causal relationships between faults and protective devices are defined as fuzzy relations. The uncertainties existing in the fault diagnosis are figured out using the possibility theory and the possibility measure is associated with the fuzzy relation to evaluate the possibilities of faults. Besides, the knowledge base in the expert system is described and explained. In this way, multiple-fault can be handled easily and simultaneously together with single faults.

• 한국정보과학회논문지:소프트웨어및응용
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• 제26권9호
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• pp.1114-1124
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• 1999

클러스터링은 동일한 클러스터에 속하는 데이타들 간에는 유사도가 크도록 하고 다른 클러스터에 속하는 데이타들 간에는 유사도가 작도록 주어진 데이타를 몇 개의 클러스터로 묶는 것이다. 어떤 대상을 기술하는 데이타는 수치 속성뿐만 아니라 정성적인 비수치 속성을 갖게 되고, 이들 속성값은 관측 오류, 불확실성, 주관적인 판정 등으로 인해서 정확한 값으로 주어지지 않고 애매한 값으로 주어지는 경우가 많다. 본 논문에서는 애매한 값을 퍼지값으로 표현하는 수치 속성과 비수치 속성을 포함한 데이타에 대한 비유사도 척도를 제안하고, 이 척도를 이용하여 퍼지값을 포함한 데이타에 대하여 퍼지 클러스터링하는 방법을 소개한 다음, 이를 이용한 실험 결과를 보인다. Abstract The objective of clustering is to group a set of data into some number of clusters in a way to minimize the similarity between data belonging to different clusters and to maximize the similarity between data belonging to the same cluster. Many data for real world objects consist of numeric attributes and non-numeric attributes whose values are fuzzily described due to observation error, uncertainty, subjective judgement, and so on. This paper proposes a dissimilarity measure applicable to such data and then introduces a fuzzy clustering method for such data using the proposed dissimilarity measure. It also presents some experiment results to show the applicability of the proposed clustering method and dissimilarity measure.

• International Journal of Quality Innovation
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• 제5권2호
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• pp.45-62
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• 2004

Any business activities may have impact on environment to a certain extent. Enterprises must find appropriate approaches to measure the impact on these environmental aspects, which can be used as the basis to direct enterprises' efforts to improve the environmental impact. The method used to evaluate significant factors in life cycle assessment standards is the one most commonly used by enterprises in general to measure environmental impact. By this method, the decisive factors of each environmental aspect are given scores according to the preset scoring standard of the organization. The scores are added up for each aspect and ranked to assess major environmental aspects. The drawback of this assessment method, that is, it ignores the degree to which each of these factors affects the environment, results in poor credibility. Therefore, this study attempts to solve some qualitative problems by applying to fuzzy theory, in particular, by identifying appropriate fuzzy numbers through fuzzy sets and membership function. Moreover, the study seeks to obtain a crisp value in the process of defuzzifization in order to make up for the shortfall of the original method in dealing with relative weight of decisive factors and thus increase its applicability and credibility. The department of light production of an electronics company is used as an example in this study to measure environmental aspects by employing both the traditional significant factor method and the fuzzy environmental impact assessment model proposed in this study. Based on verification and comparison of results, the model proposed in this study is more feasible as it reduces partiality in decision-making by taking the relative weights of decisive factors into consideration.

• 정보처리학회논문지B
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• 제8B권5호
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• pp.463-468
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• 2001

상대적 소속 함수(RMF)에 기반을 둔 새로운 유사성 측도를 제안한다. 본 논문에서는 RMF는 퍼지 부분 집합간의 상대성을 쉽게 나타내기 위해 제시되었다. 이러한 RMF의 형태는 매개변수값들에 따라 결정되기 때문에 매개변수 값들만을 조정해 줌으로써 퍼지 부분 집합간의 상대성을 쉽게 나타낼 수 있다. 그러므로 퍼지 부분 집합을 이용해 주관성을 표현할 때 개인이나 문화차이간의 상대성을 쉽게 반영해 줄수 있다. 이 경우이들 매개변수들은 퍼비 부분 집합의 구조를 결정해 주는 특징점들이라고 할수 있다. 결과적으로 퍼지 부분 집합간의 유사성 정도가 RMF의 매개변수들을 이용해서 빠르게 계산될 수 있다. RMF에 의해 퍼지 부분 집합간의 유사성 정도를 계산하기 위해 유클리디안 거리를 사용한다. 한편, 제안된 유사성 측도의 응용 분야로 새로운 언어 근사 방법을 제시하고 수치적인 예를 보여준다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권3호
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• pp.181-187
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• 2014

Dealing with uncertainty is always a challenging problem. Intuitionistic fuzzy sets was presented to manage situations in which experts have some membership and non-membership value to assess an alternative. Hesitant fuzzy sets was used to handle such situations in which experts hesitate between several possible membership values to assess an alternative. In this paper, the concept of intuitionistic hesitant fuzzy set is introduced to provide computational basis to manage the situations in which experts assess an alternative in possible membership values and non-membership values. Distance measure is defined between any two intuitionistic hesitant fuzzy elements. Fuzzy technique for order preference by similarity to ideal solution is developed for intuitionistic hesitant fuzzy set to solve multi-criteria decision making problem in group decision environment. An example is given to illustrate this technique.

• Journal of applied mathematics & informatics
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• 제34권3_4호
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• pp.295-308
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• 2016

Depending upon the nature of the problem, different divergence measures are suitable. So it is always desirable to develop a new divergence measure. In the present work, new information divergence measure, which is exponential in nature, is introduced and characterized. Bounds of this new measure are obtained in terms of various symmetric and non- symmetric measures together with numerical verification by using two discrete distributions: Binomial and Poisson. Fuzzy information measure and Useful information measure corresponding to new exponential divergence measure are also introduced.

• 한국지능시스템학회논문지
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• 제20권2호
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• pp.292-297
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• 2010

In this paper, we introduce the notions of inconsistency p-measure, consistency p-measure and fuzziness p-measure. We discuss various properties of them. We investigate the degree of inconsistency and roughness p-measure in a decision table.

• 정보보호학회논문지
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• 제14권2호
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• pp.113-121
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• 2004

인터넷이 급속하게 발전함에 따라 침입탐지의 유형도 매우 다양해지고 복잡해졌다. 이로 인해 발생하는 피해를 막기 위해 많은 침입탐지시스템이 개발되었다. 본 논문에서는 침입탐지시스템 평가기준에 대해 퍼지적분을 이용한 평가방법을 제시하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.349-352
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• 2004

In this literature, the selection of data set among the universe set is carried out with the fuzzy entropy function. By the definition of fuzzy entropy, we have proposed the fuzzy entropy function and the proposed fuzzy entropy function is proved through the definition. The proposed fuzzy entropy function calculate the certainty or uncertainty value of data set, hence we can choose the data set that satisfying certain bound or reference. Therefore the reliable data set can be obtained by the proposed fuzzy entropy function. With the simple example we verify that the proposed fuzzy entropy function select reliable data set.