• Title/Summary/Keyword: Fuzzy Function

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Fuzzy r-minimal Continuous Functions Between Fuzzy Minimal Spaces and Fuzzy Topological Spaces

  • Min, Won-Keun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.10 no.2
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    • pp.124-127
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    • 2010
  • In this paper, we introduce the concepts of fuzzy r-minimal continuous function and fuzzy r-minimal open function between a fuzzy r-minimal space and a fuzzy topological space. We also investigate characterizations and properties for such functions.

A Study on Fuzzy Comparisons between Fuzzy Numbers Based on the Satisfaction Function (만족도 함수를 이용한 퍼지숫자의 퍼지비교에 관한 연구)

  • 이지형;이광형
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.5
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    • pp.14-20
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    • 1998
  • This paper proposes a fuzzy comparison method called the fuzzy satisfaction function. It compares two fuzzy numbers and produces a fuzzy set on [O, 11 as the comparison result. It represents the possibility that a fuzzy number is greater(smal1er) than the other with a fuzzy set on [0, I]. It is extended from the satisfaction function which compares two fuzzy numbers and generates a value in [0, 11 as the result. This paper summarizes the satisfaction function and proposes the fuzzy satisfaction function. Some numerical examples are also presented in this paper.

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Fuzzy Entropy Construction for Non-Convex Fuzzy Membership Function (비 컨벡스 퍼지 소속함수에 대한 퍼지 엔트로피구성)

  • Lee, Sang-H;Kim, Jae-Hyung;Kim, Sang-Jin
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2008.04a
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    • pp.21-22
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    • 2008
  • Fuzzy entropy is designed for non-convex fuzzy membership function using well known Hamming distance measure. Design procedure of convex fuzzy membership function is represented through distance measure, furthermore characteristic analysis for non-convex function are also illustrated. Proof of proposed fuzzy entropy is discussed, and entropy computation is illustrated.

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Selection of data set with fuzzy entropy function (퍼지 엔트로피 함수를 이용한 데이터추출)

  • Lee, Sang-Hyuk;Cheon, Seong-Pyo;Kim, Sung-Shin
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.04a
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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.

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Selection of data set with fuzzy entropy function

  • Lee, Sang-Hyuk;Cheon, Seong-Pyo;Kim, Sung shin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.5
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    • pp.655-659
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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, the fuzzy entropy function is proposed 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.

Analysis of Fuzzy Entropy and Similarity Measure for Non Convex Membership Functions

  • Lee, Sang-H.;Kim, Sang-Jin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.1
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    • pp.4-9
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    • 2009
  • Fuzzy entropy is designed for non convex fuzzy membership function using well known Hamming distance measure. Design procedure of convex fuzzy membership function is represented through distance measure, furthermore characteristic analysis for non convex function are also illustrated. Proof of proposed fuzzy entropy is discussed, and entropy computation is illustrated.

On statistical testing for fuzzy hypotheses with fuzzy data (퍼지자료에 관한 퍼지가설의 통계적 검정)

  • 최규탁;이창은;강만기
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.255-258
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    • 2000
  • We prepose fuzzy statistical test of fuzzy hypotheses membership function with fuzzy number data. Finding the maximum grade of the meeting point for fuzzy hypotheses membership function and membership function of confidence interval. By the maximum grade, we obtain the results to acceptance or reject for the test of fuzzy hypotheses.

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Fuzzy Test for the Fuzzy Regression Coefficient (퍼지회귀계수에 관한 퍼지검정)

  • 강만기;정지영;최규탁
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.05a
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    • pp.29-33
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    • 2001
  • We propose fuzzy least-squares regression analysis by few error term data and test the slop by fuzzy hypotheses membership function for fuzzy number data with agreement index. Finding the agreement index by area for fuzzy hypotheses membership function and membership function of confidence interval, we obtain the results to acceptance or reject for the test of fuzzy hypotheses.

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