• 제목/요약/키워드: Fuzzy Set-Fuzzy Systems

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퍼지연속함수와 퍼지 집합값 함수 (Fuzzy Continuous Mappings and Fuzzy Set-Valued Mappings)

  • J.H. Ryou;K. Hur
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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    • pp.319-323
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    • 2001
  • First, we study some properties of F-continuities. Second, we introduce the concept of fuzzy set-valued mappings and study some properties of fuzzy set-valued mappings and fuzzy set-valued continuous mappings. Finally, we Introduce the concept of fuzzy semi-continuous of fuzzy set-valued mappings and investigate their some properties.

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Intuitionistic Fuzzy Topology and Intuitionistic Fuzzy Preorder

  • Yun, Sang Min;Lee, Seok Jong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제15권1호
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    • pp.79-86
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    • 2015
  • This paper is devoted to finding relationship between intuitionistic fuzzy preorders and intuitionistic fuzzy topologies. For any intuitionistic fuzzy preordered space, an intuitionistic fuzzy topology will be constructed. Conversely, for any intuitionistic fuzzy topological space, we obtain an intuitionistic fuzzy preorder on the set. Moreover, we will show that the family of all intuitionistic fuzzy preorders on an underlying set has a very close link to the family of all intuitionistic fuzzy topologies on the set satisfying some extra condition.

Calculation of Data Reliability with Entropy for Fuzzy Sets

  • Wang, Hongmei;Lee, Sang-Hyuk
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제9권4호
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    • pp.269-274
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    • 2009
  • Measuring uncertainty for fuzzy sets has been carried out by calculating fuzzy entropy. Fuzzy entropy of fuzzy set is derived with the help of distance measure. The distance proportional value between the fuzzy set and the corresponding crisp set is designed as the fuzzy entropy. The usefulness is verified by proving the proposed entropy. Generally, fuzzy entropy contains the complementary characteristics that the fuzzy entropies of fuzzy set and complementary fuzzy set have the same entropies. Discrepancy that low fuzzy entropy did not guarantee the data certainty was overcome by modifying fuzzy entropy formulation. Obtained fuzzy entropy is analyzed and discussed through simple example.

퍼지 속성 집합을 이용한 데이터 분석 모델 (Data Analysis Model using the Fuzzy Property Set)

  • 이진호;이전영
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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    • pp.252-255
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    • 1997
  • In this paper, we will propose the methodology of data analysis using the fuzzy property set model. In real world, the data can be represented with the object. $\theta$. and the property, $\pi$, and its has-property relation, P. Then, the conceptual space can be defined with the chosen properties. Each object has a unique location in the conceptual space. In Fuzzy mode, the fuzzy property, and fuzzy conceptual space can be redefined. To analyze data using the fuzzy property set model, the rough set need to be defined in the fuzzy conceptual space.

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Fuzzy Sets and Decision Marking in Nuclear Science

  • Ruan, D.
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.1058-1061
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    • 1993
  • Fuzzy set theory has been extensively researched in various fields of engineering. In nuclear science, a significant influence of fuzzy sets can be noticed. However, applications of fuzzy set theory to nuclear engineering is novel. In this paper, we start with a basic statement of the decision-making process based on fuzzy set theory, and then apply it to nuclear science with some practical applications (a fuzzy decision making in an accidental release to the atmosphere as well as in a problem of land suitability classification). We believe that the use of fuzzy set theory in nuclear science has potential advantages.

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Fuzzy γ-Quasi Open Set and Fuzzy γ-Quasi Continuity

  • Min, Won-Keun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제10권3호
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    • pp.200-202
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    • 2010
  • In this paper, we introduce the concept of fuzzy ${\gamma}$-quasi open sets which are generalizations of fuzzy ${\gamma}$-open sets, and obtain some basic properties of such fuzzy sets. Also we introduce and study the concepts of fuzzy ${\gamma}$-quasi continuous mapping and fuzzy ${\gamma}$-quasi open(closed) mapping.

Similarity Analysis Between Fuzzy Set and Crisp Set

  • Park, Hyun-Jeong;Lee, Sang-Hyuk.
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제7권4호
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    • pp.295-300
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    • 2007
  • The similarity analysis for fuzzy set pair or crisp set pair are carried out. The similarity measure that is based on distance measure is derived and proved. The proposed similarity measure is considered with the help of analysis for uncertainty or certainty part of the membership functions. The usefulness of proposed similarity is verified through the computation of similarity between fuzzy set and crisp set or fuzzy set and fuzzy set. Our results are also compared with those of previous similarity measure which is based on fuzzy number.

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

  • Lee, Sang-Hyuk;Cheon, Seong-Pyo;Kim, Sung-Shin
    • 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.

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Selection of data set with fuzzy entropy function

  • Lee, Sang-Hyuk;Cheon, Seong-Pyo;Kim, Sung shin
    • 한국지능시스템학회논문지
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    • 제14권5호
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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.