• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권4호
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• pp.367-371
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• 2005

The similarity measure is derived using fuzzy entropy and distance measure. By the elations of fuzzy entropy, distance measure, and similarity measure, we first obtain the fuzzy entropy. And with both fuzzy entropy and distance measure, similarity measure is obtained., We verify that the proposed measure become the similarity measure.

• 한국통신학회논문지
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• 제30권9C호
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• pp.854-859
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• 2005

모호함의 측도를 위하여 퍼지 엔트로피와 거리측도 그리고 유사측도와의 관계를 이용하여 새로운 퍼지 측도를 제안하였다. 제안된 퍼지 엔트로피는 거리측도를 이용하여 구성된다. 거리측도는 일반적으로 사용되는 해밍 거리를 이용하였다. 또한 집합사이의 유사성을 측정하기 위한 유사측도를 거리 측도를 이용하여 구성하였고, 제안한 퍼지 엔트로피와 유사측도를 증명을 통하여 타당성을 확인하였다.

• 한국지능시스템학회논문지
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• 제15권5호
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• pp.521-526
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• 2005

모호함의 측도를 위하여 퍼지 엔트로피와 거리측도 그리고 유사측도와의 관계를 이용하여 새로운 퍼지 측도를 제안하였다. 제안된 퍼지 엔트로피는 거리측도를 이용하여 구성된다. 거리측도는 일반적으로 사용되는 해밍 거리를 이용하였다. 또한 집합사이의 유사성을 측정하기 위한 유사측도를 거리 측도를 이용하여 구성하였고, 제안한 퍼지 엔트로피와 유사측도를 증명을 통하여 타당성을 확인하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.9-12
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• 2002

Representation and quantification of fuzziness are required for the uncertain system modelling and controller design. Conventional results show that entropy of fuzzy sets represent the fuzziness of fuzzy sets. In this literature, the relations of fuzzy enropy, distance measure and similarity measure are discussed, and distance measure is proposed. With the help of relations of fuzzy enropy, distance measure and similarity measure, fuzzy entropy is represented by the newly proposed distance measure. With simple fuzzy set, example is illustrated.

• Nuclear Engineering and Technology
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• 제33권3호
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• pp.270-282
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• 2001

A simple measure of uncertainty importance based on normalized metric distance to quantify the entire change of cumulative distribution functions (CDFs) has been developed for use in probability safety assessments (PSAs). The metric distance measure developed in this study reflects the relative impact of distributional changes of inputs on the change of an output distribution, white most of the existing uncertainty importance measures reflect the magnitude of relative contribution of input uncertainties to the output uncertainty. Normalization is made to make the metric distance measure a dimensionless quantity. The present measure has been evaluated analytically for various analytical distributions to examine its characteristics. To illustrate the applicability and strength of the present measure, two examples are provided. The first example is an application of the present measure to a typical problem of a system fault tree analysis and the second one is for a hypothetical non-linear model. Comparisons of the present result with those obtained by existing uncertainty importance measures show that the metric distance measure is a useful tool to express the measure of uncertainty importance in terms of the relative impact of distributional changes of inputs on the change of an output distribution.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.543-546
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• 2003

Representation and quantification of fuzziness are required for the uncertain system modelling and controller design. Conventional results show that entropy of fuzzy sets represent the fuzziness of fuzzy sets. In this literature, the relations of fuzzy enropy, distance measure and similarity measure are discussed, and distance measure is proposed. With the help of relations of fuzzy entropy, distance measure and similarity measure, fuzzy entropy is proposed by the distance measure. Finally, proposed entropy is applied to measure the fault signal of induction machine.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.254-258
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• 2004

In this paper, we propose a robust speech recognition system under noisy environments. Since the presence of noise severely degrades the performance of speech recognition system, it is important to design the robust speech recognition method against noise. The proposed method adopts a new distance measure technique based on stochastic probability instead of conventional method using minimum error. For evaluating the performance of the proposed method, we compared it with conventional distance measure for the 10-isolated Korean digits with car noise. Here, the proposed method showed better recognition rate than conventional distance measure for the various car noisy environments.

• International Journal of Advanced Culture Technology
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• 제9권3호
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• pp.298-304
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• 2021

Currently, to prevent the spread of COVID-19 virus infection, gathering of more than 5 people in the same space is prohibited. The purpose of this paper is to measure the distance between objects using the Yolov5 model for processing real-time images with OpenCV in order to restrict the distance between several people in the same space. Also, Utilize Euclidean distance calculation method in DeepSORT and OpenCV to minimize occlusion. In this paper, to detect the distance between people, using the open-source COCO dataset is used for learning. The technique used here is using the YoloV5 model to measure the distance, utilizing DeepSORT and Euclidean techniques to minimize occlusion, and the method of expressing through visualization with OpenCV to measure the distance between objects is used. Because of this paper, the proposed distance measurement method showed good results for an image with perspective taken from a higher position than the object in order to calculate the distance between objects by calculating the y-axis of the image.

• 한국지능시스템학회논문지
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• 제17권4호
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• pp.455-459
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• 2007

Interval-valued fuzzy sets were suggested for the first time by Gorzafczany(1983) and Turksen(1986). Based on this, Zeng and Li(2006) introduced concepts of similarity measure and entropy on interval-valued fuzzy sets which are different from Bustince and Burillo(1996). In this paper, by using Choquet integral with respect to a fuzzy measure, we introduce distance measure and similarity measure defined by Choquet integral on interval-valued fuzzy sets and discuss some properties of them. Choquet integral is a generalization concept of Lebesgue inetgral, because the two definitions of Choquet integral and Lebesgue integral are equal if a fuzzy measure is a classical measure.

• 한국융합학회논문지
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• 제5권4호
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• pp.155-161
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• 2014

We survey the relation of fuzzy entropy measure and similarity measure. Each measure represents features of data uncertainty and certainty between comparative data group. With the help of one-to-one correspondence characteristics, distance measure and similarity measure have been expressed by the complementary characteristics. We construct similarity measure using distance measure, and verification of usefulness is proved. Furthermore analysis of similarity measure from fuzzy entropy measure is also discussed.