• 제목/요약/키워드: Fuzzy measures

검색결과 219건 처리시간 0.02초

퍼지이론 이용한 적 위협수준평가 모델개발 연구 (A Study on the Threat-Level Assessment Model Developmnet using Fuzzy Theory)

  • 장동학;홍윤기
    • 한국산학기술학회논문지
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    • 제12권7호
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    • pp.3245-3250
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    • 2011
  • 이 연구는 지휘관의 위협평가시 의사결정을 도와주기 위한 모델을 제시하였다. 이를 위해 해양조건, 적 함정 제원, 전략환경 3가지 상위평가항목으로 위협요소를 설정하였다. 퍼지추론을 이용하여 각 상위항목별 위협수준을 산정한 후, 퍼지척도를 이용하여 상위평가항목별 중요도를 산정하였다. 마지막으로 상위평가항목의 위협수준을 종합하기 위해 choquet의 퍼지적분을 사용하였다.

쇼케이적분에서 퍼지 프리인벡스에 관한 연구 (On fuzzy preinvexity in Choquet integrals)

  • 장이채;김현미
    • 한국지능시스템학회논문지
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    • 제18권2호
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    • pp.183-186
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    • 2008
  • 우리는 퍼지 인벡스 집합, 퍼지 프리인벡스 함수, 퍼지 유사-프리인벡스 함수와 퍼지 로그 프리인벡스 함수를 생각한다. 무로푸시 등은 쇼케이적분과 그 응용에 관한 연구를 계속해오고 있다. 이 논문에서는 다음과 같은 쇼케이적분에서의 성질들을 조사한다: 퍼지 프리인벡스성, 퍼지 유사-프리인벡스성과 퍼지 로그 프리인벡스성, 즉, 쇼케이 적분에 의해 정의되는 범함수의 성질들임 더욱이 쇼케이적분의 제센 형태 부등식을 증명한다.

퍼지컬러 모델을 이용한 컬러 데이터 클러스터링 알고리즘1 (Color Data Clustering Algorithm using Fuzzy Color Model)

  • Kim, Dae-Won;Lee, Kwang H.
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
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    • pp.119-122
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    • 2002
  • The research Interest of this paper is focused on the efficient clustering task for an arbitrary color data. In order to tackle this problem, we have tiled to model the inherent uncertainty and vagueness of color data using fuzzy color model. By laking a fuzzy approach to color modeling, we could make a soft decision for the vague regions between neighboring colors. The proposed fuzzy color model defined a three dimensional fuzzy color ball and color membership computation method with the two inter-color distance measures. With the fuzzy color model, we developed a new fuzzy clustering algorithm for an efficient partition of color data. Each fuzzy cluster set has a cluster prototype which is represented by fuzzy color centroid.

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Hausdorff Distance를 이용한 퍼지 하드웨어 구현 (Fuzzy Hardware Implementation using the Hausdorff Distance)

  • 김종만;변오성;문성룡
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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    • pp.147-150
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    • 2000
  • Hausdorff distance(HD) commonly used measures for object matching, and calculates the distance between two point set of pixels in two-dimentional binary images without establishing correspondence. And it is realized as the image filter applying the fuzzy. In this paper, the fuzzy hardware realizes in order to construct the image filter applying HD, also, propose as the method for the noise removal using it in the image. MIN-MAX circuit designs the circuit using MAX-PLUS, and the fuzzy HD hardware results are obtained to the simulation. And then, the previous computer simulation is confirmed to the result by using MATLAB.

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Subsethood Measures Defined by Choquet Integrals

  • Jang, Lee-Chae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제8권2호
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    • pp.146-150
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    • 2008
  • In this paper, we consider concepts of subsethood measure introduced by Fan et al. [2]. Based on this, we give various subsethood measure defined by Choquet integral with respect to a fuzzy measure on fuzzy sets which is often used in information fusion and data mining as a nonlinear aggregation tool and discuss some properties of them. Furthermore, we introduce simple examples.

퍼지추론을 이용한 설비가동상태진단 모델 연구 (Development of Equipment Operating Condition Diagnosis Model Using the Fuzzy Inference)

  • 정영득;박주식
    • 산업경영시스템학회지
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    • 제28권4호
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    • pp.109-115
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    • 2005
  • In the study, Methods for operating measures in equipment security to find out dangerousness timely in the system and to need for the prevention and measures. The method for analyzing and reconstructing the causes of accident of equipment in site, and try to save the information of site in real-time and to analyze the state of equipment to look for the factors of accidents. By this analysis, one plan for efficiency of production, Equipment Fault Diagnosis Management and security is integrating and building module of using the Fuzzy Inference based on fuzzy theory. The case study is applied to the industrial electric motors that are necessarily used to all manufacturing equipment. Using the sensor for temperature is attached to gain the site information in real time and to design the hardware module for signal processing. In software, realize the system supervising and automatically saving to management data base by the algorithm based in fuzzy theory from the existing manual input system

FUZZY REGRESSION MODEL WITH MONOTONIC RESPONSE FUNCTION

  • Choi, Seung Hoe;Jung, Hye-Young;Lee, Woo-Joo;Yoon, Jin Hee
    • 대한수학회논문집
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    • 제33권3호
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    • pp.973-983
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    • 2018
  • Fuzzy linear regression model has been widely studied with many successful applications but there have been only a few studies on the fuzzy regression model with monotonic response function as a generalization of the linear response function. In this paper, we propose the fuzzy regression model with the monotonic response function and the algorithm to construct the proposed model by using ${\alpha}-level$ set of fuzzy number and the resolution identity theorem. To estimate parameters of the proposed model, the least squares (LS) method and the least absolute deviation (LAD) method have been used in this paper. In addition, to evaluate the performance of the proposed model, two performance measures of goodness of fit are introduced. The numerical examples indicate that the fuzzy regression model with the monotonic response function is preferable to the fuzzy linear regression model when the fuzzy data represent the non-linear pattern.

An empirical comparison of static fuzzy relational model identification algorithms

  • Bae, Sang-Wook;Lee, Kee-Sang;Park, Gwi-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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    • pp.146-151
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    • 1994
  • An empirical comparison of static fuzzy relational models which are identified with different fuzzy implication operators and inferred by different composition operators is made in case that all the information is represented by the fuzzy discretization. Four performance measures (integral of mean squared error, maximal error, fuzzy equality index and mean lack of sharpness) are adopted to evaluate and compare the quality of the fuzzy relational models both at the numerical level and logical level. As the results, the fuzzy implication operators useful in various fuzzy modeling problems are discussed and it is empirically shown that the selection of data pairs is another important factor for identifying the fuzzy model with high quality.

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Using Fuzzy Rating Information for Collaborative Filtering-based Recommender Systems

  • Lee, Soojung
    • International journal of advanced smart convergence
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    • 제9권3호
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    • pp.42-48
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    • 2020
  • These days people are overwhelmed by information on the Internet thus searching for useful information becomes burdensome, often failing to acquire some in a reasonable time. Recommender systems are indispensable to fulfill such user needs through many practical commercial sites. This study proposes a novel similarity measure for user-based collaborative filtering which is a most popular technique for recommender systems. Compared to existing similarity measures, the main advantages of the suggested measure are that it takes all the ratings given by users into account for computing similarity, thus relieving the inherent data sparsity problem and that it reflects the uncertainty or vagueness of user ratings through fuzzy logic. Performance of the proposed measure is examined by conducting extensive experiments. It is found that it demonstrates superiority over previous relevant measures in terms of major quality metrics.

퍼지 평가의 통합특성에 관하여 (On the Fuzzy Approach to Integrated Evaluation of Complex Systems)

  • 이철영;임봉택
    • 한국항만학회지
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    • 제13권1호
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    • pp.79-86
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    • 1999
  • This paper deals with the evaluation problem of complex systems by introducing a fuzzy approach. The authors are functionally supposing a hierarchical structure model of a complex system and give light on the following problems. First for the purpose of clarifying the characteristics of measures the property and differences between two method such as linear and fuzzy viewpoint are discussed through two level-down evaluation process. Second the integrated evaluation process which keeps reversibility between hierarchical levels is discussed and obtained some necessary conditions for reversibility of fuzzy evaluation. From these results it is expected that the fuzzy approach overcomes partly the limitation of reductionism at the hierarchical evaluation of complex systems.

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