• Title/Summary/Keyword: Choquet integrals

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Some properties of Choquet distance measures for interval-valued fuzzy numbers (구간치 퍼지수 상의 쇼케이 거리측도에 관한 성질)

  • Jang, Lee-Chae;Kim, Won-Joo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.7
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    • pp.789-793
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    • 2005
  • Interval-valued fuzzy sets were suggested for the first time by Gorzalczang(1983) and Turken(19a6). Based on this, Wang and Li offended their operations on interval-valued fuzzy numbers. Recently, Hong(2002) generalized results of Wang and Li and extended to interval-valued fuzzy sets with Riemann integral. In this paper, using Choquet integrals with respect to a fuzzy measure instead of Riemann integrals with respect to a classical measure, we define a Choquet distance measure for interval-valued fuzzy numbers and investigate its properties.

A study on interval-valued necessity measures through the Choquet integral criterian (쇼케이 적분 기준을 통한 구간치 필요측도에 관한 연구)

  • Jang, Lee-Chae;Kim, Tae-Kyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.3
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    • pp.350-354
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    • 2009
  • Y. R$\acute{e}$ball$\acute{e}$[Fuzzy Sets and Systems, vol.157, pp.3025-2039, 2006] discussed the representation of necessity measure through the Choquet integral criterian. He also considered a decision maker who ranks necessity measures related with Choquet integral representation. Our motivation of this paper is that a decision maker have an "ambiguity" necessity measure to present preferences. In this paper, we discuss the representation of interval-valued necessity measures through the Choquet integral criterian.

Structural characterizations of monotone interval-valued set functions defined by the interval-valued Choquet integral (구간치 쇼케이적분에 의해 정의된 단조 구간치 집합함수의 구조적 성질에 관한 연구)

  • Jang, Lee-Chae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.3
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    • pp.311-315
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    • 2008
  • We introduce nonnegative interval-valued set functions and nonnegative measurable interval-valued Junctions. Then the interval-valued Choquet integral determines a new nonnegative monotone interval-valued set function which is a generalized concept of monotone set function defined by Choquet integral in [17]. We also obtained absolutely continuity of them in [9]. In this paper, we investigate some characterizations of the monotone interval-valued set function defined by the interval-valued Choquet integral, and such as subadditivity, superadditivity, null-additivity, converse-null-additivity.

A Note on Set-Valued Choquet Integrals

  • Hong, Dug-Hun;Kim, Kyung-Tae
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.1041-1044
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    • 2005
  • Recently, Zhang et al.(Fuzzy Sets and Systems 147(2004) 475-485) proved Fatou's lemma and Lebesgue dominated convergence theorem under some conditions of fuzzy measure. In this note, we show that these conditions of fuzzy measure is essential to prove Fatou's lemma and Lebesgue dominated convergence theorem by examples

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A note on entropy defined by Choquet integral on interval-valued fuzzy sets (구간치 퍼지집합상에서 쇼케이적분에 의해 정의된 엔트로피에 관한 연구)

  • Jang, Lee-Chae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.2
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    • pp.149-153
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    • 2007
  • In this paper, we consider interval-valued fuzzy sets which were suggested by Wang and Li(1998) and Turksen(1986) and investigate entropy defined by Choquet integral on interval-valued fuzzy sets. Furthermore, we discuss some properties of them and give some examples related this entropy. This tool has drawn much attention due to numerous applications areas, such as decision making and information theory on interval-valued fuzzy sets.

A note on entropy defined by Choquet integral on interval-valued fuzzy sets (구간치 퍼지집합상에서 쇼케이적분에 의해 정의된 엔트로피에 관한 연구)

  • Jang, Lee-Chae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2006.11a
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    • pp.157-160
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    • 2006
  • In this paper, we consider interval-valued fuzzy sets which were suggested by Wang and Li(1998) and Turksen(1986) and investigate entropy defined by Choquet integral on interval-valued fuzzy sets. Furthermore, we discuss some properties of them and give some examples related this entropy.

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Incomplete Information Recognition Using Fuzzy Integrals Aggregation: With Application to Multiple Matchers for Image Verification

  • Kim, Seong H.;M. Kamel
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.28-31
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    • 2003
  • In the present work, a main purpose is to propose a fuzzy integral-based aggregation framework to complementarily combine partial information due to lack of completeness. Based on Choquet integral (CI) viewed as monotone expectation, we take into account complementary, non-interactive, and substitutive aggregations of different sources of defective information. A CI-based system representing upper, conventional, and lower expectations is designed far handling three aggregation attitudes towards uncertain information. In particular, based on Choquet integrals for belief measure, probability measure, and plausibility measure, CI$\_$bi/-, CI$\_$pr/ and CI$\_$pl/-aggregator are constructed, respectively. To illustrate a validity of proposed aggregation framework, multiple matching systems are developed by combining three simple individual template-matching systems and tested under various image variations. Finally, compared to individual matchers as well as other traditional multiple matchers in terms of an accuracy rate, it is shown that a proposed CI-aggregator system, {CI$\_$bl/-aggregator, CI$\_$pl/-aggregator, Cl$\_$pl/-aggregator}, is likely to offer a potential framework for either enhancing completeness or for resolving conflict or for reducing uncertainty of partial information.

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Evaluation of Human Interface using Fuzzy Measures and Fuzzy Integrals (퍼지척도 퍼지적분을 이용한 휴면 인터페이스의 평가)

  • 손영선
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.31-36
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    • 1998
  • This paper proposes a method to select essential elements in a human evaluation model using the Choquet integral based on fuzzy measures and applies the model to the evaluation of human interface. Three kinds of concepts, Increment Degree, average of Increment Degree, Necessity coefficient, are defined. The proposed method selects essential elements by the use of the Relative necessity coefficient. The proposed method is applied to the analysis of human interface. In the experiment, (1) a warning sound, (2)a color vision, (3) the size of working area, (4) a response of confirmation, are considered as human interface elements. subjects answer the questionnarie after the experiment. From the data of questionnaire, fuzzy measures are identified and are applied to the proposed model. effectiveness of the proposed model is confirmed by the comparison of human interface elements extracted from the proposed model and those from the questionnarie.

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Application of fuzzy measure and fuzzy integrals model to evaluation of human interface

  • Sohn, Young-Sun;Onisawa, Takehisa
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.787-790
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    • 1997
  • This paper proposes a method which selects essential elements in a human evaluation model using the Choquet integral based on fuzzy measures, and applies the model to the evaluation of human interface. Three kinds of concepts are defined to select essential elements. Increment Degree implies the increment degree from fuzzy measures of composed elements to the fuzzy measure of a combined element. Average of Increment Degree of an element means the relative possibility of superadditivity of the fuzzy measure of each combined element. Necessity Degree means the selection degree of each combined element as a result of the human evaluation. A task experiment, which consists of a static work and two dynamic works, is performed by the use of some human interfaces. In the experiment, (1) a warning sound which gives an attention to subjects, (2) a color vision which can be distinguished easily or not, (3) the size of working area and (4) a response of confirmation that is given from an interface, are considered as human interface elements. Subjects answer the questionnaire after the experiment. From the data of the questionnaire, fuzzy measures are identified and are applied to the proposed model. Effectiveness of the proposed model is confirmed by the comparison of human interface elements extracted from the proposed model and those from the questionnaire.

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