• 제목/요약/키워드: (fuzzy) S-map

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퍼지 (r, s)-semi-preopen 집합과 퍼지 (r, s)-semi-precontinuous 함수 (Fuzzy (r, s)-semi-preopen sets and fuzzy (r, s)-semi-precontinuous maps)

  • 이석종;김진태
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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    • pp.179-182
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    • 2007
  • In this paper, we introduce the concepts of fuzzy (r, s)-semi-preopen sets and fuzzy (r, s)-semi-precontinuous maps on intuitionistic fuzzy topological spaces in Sostak's sense. The relations among fuzzy (r, s)-semicontinuous, fuzzy (r, s)-precontinuous, and fuzzy (r, s)-semi-precontinuous maps are discussed. The concepts of fuzzy (r, s)-semi-preinterior, fuzzy (r, s)-semi-preclosure, fuzzy (r, s)-semi-preneighborhood, and fuzzy (r, s)-quasi-semi-preneighborhood are given. Using these concepts, the characterization for the fuzzy (r, s)-semi-precontinuous map is obtained. Also, we introduce the notions of fuzzy (r, s)-semi-preopen and fuzzy (r, s)-semi-preclosed maps on intuitionistic fuzzy topological spaces in Sostak's sense, and then we investigate some of their characteristic properties.

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Fuzzy maps

  • Chung, S. H.
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.376-379
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    • 1998
  • We introduce the concept of a 'fuzzy' map between sets by modifying the concept of the extension principle introduced by Dubois and Prade in [1] and study their properties. Using these we generalize Goguen's and Zadeh's extension principles in [2] and [3].

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CATEGORICAL PROPERTIES OF INTUITIONISTIC FUZZY TOPOLIGICAL SPACES

  • Lee, Seok-Jong;Lee, Eun-Pyo
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.225-230
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    • 1998
  • In this paper, we introduce the concepts of intuitionistic fuzzy points and intuitionistic fuzzy neighborhoods. We investigate properties of continuous, open and closed maps in the intuitionistic fuzzy topological spaces, and show that the category of Chang's fuzzy topological spaces is a bireflective full subcategory of that of intuitionistic fuzzy topogical spaces.

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Fuzzy Inference Mechanism Based on Fuzzy Cognitive Map for B2B Negotiation

  • Lee, Kun-Chang;Kang, Byung-Uk
    • 한국전자거래학회:학술대회논문집
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    • 한국전자거래학회 2004년도 e-Biz World Conference
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    • pp.134-149
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    • 2004
  • This paper is aimed at proposing a fuzzy inference mechanism to enhancing the quality of cognitive map-based inference. Its main virtue lies in the two mechanisms: (1) a mechanism for avoiding a synchronization problem which is often observed during inference process with traditional cognitive map, and (2) a mechanism for fuzzifying decision maker's subjective judgment. Our proposed fuzzy inference mechanism (FIM) is basically based on the cognitive map stratification algorithm which can stratify a cognitive map into number of strata and then overcome the synchronization problem successfully. Besides, the proposed FIM depends on fuzzy membership function which is administered by decision maker. With an illustrative B2B negotiation problem, we applied the proposed FIM, deducing theoretical and practical implications. Implementation was conducted by Matlab language.

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NEW KINDS OF OPEN MAPPINGS VIA FUZZY NANO M-OPEN SETS

  • V. KALAIYARASAN;S. TAMILSELVAN;A. PRABHU;C. JOHN SUNDAR
    • Journal of applied mathematics & informatics
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    • 제41권3호
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    • pp.525-540
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    • 2023
  • In this paper, we introduce the concept of fuzzy nano M open and fuzzy nano M closed mappings in fuzzy nano topological spaces. Also, we study about fuzzy nano M Homeomorphism, almost fuzzy nano M totally mappings, almost fuzzy nano M totally continuous mappings and super fuzzy nano M clopen continuous functions and their properties in fuzzy nano topological spaces. By using these mappings, we can able to extended the relation between normal spaces and regular spaces in fuzzy nano topological spaces.

강화학습의 Q-learning을 위한 함수근사 방법 (A Function Approximation Method for Q-learning of Reinforcement Learning)

  • 이영아;정태충
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제31권11호
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    • pp.1431-1438
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    • 2004
  • 강화학습(reinforcement learning)은 온라인으로 환경(environment)과 상호작용 하는 과정을 통하여 목표를 이루기 위한 전략을 학습한다. 강화학습의 기본적인 알고리즘인 Q-learning의 학습 속도를 가속하기 위해서, 거대한 상태공간 문제(curse of dimensionality)를 해결할 수 있고 강화학습의 특성에 적합한 함수 근사 방법이 필요하다. 본 논문에서는 이러한 문제점들을 개선하기 위해서, 온라인 퍼지 클러스터링(online fuzzy clustering)을 기반으로 한 Fuzzy Q-Map을 제안한다. Fuzzy Q-Map은 온라인 학습이 가능하고 환경의 불확실성을 표현할 수 있는 강화학습에 적합한 함수근사방법이다. Fuzzy Q-Map을 마운틴 카 문제에 적용하여 보았고, 학습 초기에 학습 속도가 가속됨을 보였다.

ON L-FUZZY ALMOST PRECONTINUOUS FUNCTIONS

  • Min, Won-Keun
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제3권1호
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    • pp.53-58
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    • 1996
  • In 1981, R . Badard introduced the notion of fuzzy pretopological spaces and their representation[1]. And in 1992, R. Badard, et al. introduced the L-fuzzy pretopological spaces and studied properties of continuity, open map, closed map, and homeomorphism in L-fuzzy pretopological spaces. In this paper we introduce and study the concepts of almost continuous functions and weakly pre-continuous functions on L-fpts's.(omitted)

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효율적인 퍼지 아이디 기반 암호화 방법 (Efficient Fuzzy Identity-Based Encryption Scheme)

  • 이광수;이동훈
    • 한국정보통신설비학회:학술대회논문집
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    • 한국정보통신설비학회 2008년도 정보통신설비 학술대회
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    • pp.563-565
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    • 2008
  • In this paper, we construct an efficient fuzzy identity-based encryption scheme in the random oracle model. The fuzzy identity-based encryption is an extension of identity-based encryption schemes where a user's public key is represented as his identity. Our construction requires constant number of bilinear map operations for decryption and the size of private key is small compared with the previous fuzzy identity-based encryption of Sahai-Waters. We also presents that our fuzzy identity-based encryption can be converted to attribute-based encryption schemes.

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데이터 마이닝과 퍼지인식도 기반의 인과관계 지식베이스 구축에 관한 연구 (A Study on the Development of Causal Knowledge Base Based on Data Mining and Fuzzy Cognitive Map)

  • Kim, Jin-Sung
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
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    • pp.247-250
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    • 2003
  • Due to the increasing use of very large databases, mining useful information and implicit knowledge from databases is evolving. However, most conventional data mining algorithms identify the relationship among features using binary values (TRUE/FALSE or 0/1) and find simple If-THEN rules at a single concept level. Therefore, implicit knowledge and causal relationships among features are commonly seen in real-world database and applications. In this paper, we thus introduce the mechanism of mining fuzzy association rules and constructing causal knowledge base form database. Acausal knowledge base construction algorithm based on Fuzzy Cognitive Map(FCM) and Srikant and Agrawal's association rule extraction method were proposed for extracting implicit causal knowledge from database. Fuzzy association rules are well suited for the thinking of human subjects and will help to increase the flexibility for supporting users in making decisions or designing the fuzzy systems. It integrates fuzzy set concept and causal knowledge-based data mining technologies to achieve this purpose. The proposed mechanism consists of three phases: First, adaptation of the fuzzy membership function to the database. Second, extraction of the fuzzy association rules using fuzzy input values. Third, building the causal knowledge base. A credit example is presented to illustrate a detailed process for finding the fuzzy association rules from a specified database, demonstration the effectiveness of the proposed algorithm.

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FUZZY CLOSURE SYSTEMS AND FUZZY CLOSURE OPERATORS

  • Kim, Yong-Chan;Ko, Jung-Mi
    • 대한수학회논문집
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    • 제19권1호
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    • pp.35-51
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    • 2004
  • We introduce fuzzy closure systems and fuzzy closure operators as extensions of closure systems and closure operators. We study relationships between fuzzy closure systems and fuzzy closure spaces. In particular, two families F(S) and F(C) of fuzzy closure systems and fuzzy closure operators on X are complete lattice isomorphic.