• Title/Summary/Keyword: 퍼지론적 방법

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Fuzzy Inductive Learning System for Learning Preference of the User's Behavior Pattern (사용자 행동 패턴 선호도 학습을 위한 퍼지 귀납 학습 시스템)

  • Lee Hyong-Euk;Kim Yong-Hwi;Park Kwang-Hyun;Kim Yong-Su;June Jin-Woo;Cho Joonmyun;Kim MinGyoung;Bien Z. Zenn
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.7
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    • pp.805-812
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    • 2005
  • Smart home is one of the ubiquitous environment platforms with various complex sensor-and-control network. In this paper, a now learning methodology for learning user's behavior preference pattern is proposed in the sense of reductive user's cognitive load to access complex interfaces and providing personalized services. We propose a fuzzy inductive learning methodology based on life-long learning paradigm for knowledge discovery, which tries to construct efficient fuzzy partition for each input space and to extract fuzzy association rules from the numerical data pattern.

Web Log Analysis Technique using Fuzzy C-Means Clustering (Fuzzy C-Means클러스터링을 이용한 웹 로그 분석기법)

  • 김미라;곽미라;조동섭
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.04b
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    • pp.550-552
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    • 2002
  • 플러스터링이란 주어진 데이터 집합의 패턴들을 비슷한 성실을 가지는 그룹으로 나누어 패턴 상호간의 관계를 정립하기 위한 방법론으로, 지금가지 이를 위한 많은 알고리즘들이 개발되어 왔으며, 패턴인식, 영상 처리 등의 여러 공학 분야에 널리 적용되고 있다. FCM(Fuzzy C-Means) 알고리즘은 최소자승 기준함수(least square criterion function)에 퍼지이론을 적용만 목적함수의 반복최적화(iterative optimization)에 기반을 둔 방식으로, 하드 분할에 의한 기존의 클러스터링 방법이 승자(winner take all) 형태의 방법론을 취하는데 비하여, 각 패턴이 특정 클러스터에 속하는 소속정도를 줌으로써 보다 정확한 정보를 형성하도록 도와준다. 본 논문에서는 FCM 기법을 이용한 웹로그 분석을 하고자 한다.

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Evaluating Level of Quality for the Skyteam Cargo Services (스카이팀 카고의 서비스 품질에 대한 평가)

  • Na, Ji-Eun;Park, Yong-Hwa;Yun, Sin
    • Journal of Korean Society of Transportation
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    • v.29 no.6
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    • pp.75-83
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    • 2011
  • This research explores the relative importance of factors and service items that influence the air cargo service quality for provision services by the Skyteam Cargo in the Korean market. In general, the Skyteam Cargo provides a package of services which are different functions and operations of service such item as Equation Heavy (heavy and large express freight), Equation (small express freight), Variation (special freight), and Dimension (general freight). To carry out the research, the expert questionnaire survey, the Analytic Hierarchy Process (AHP) analysis had adopted to evaluate the level of quality for the provision air cargo operation services by the Skyteam Cargo at Incheon International Airport. Based on an expert survey and the AHP, five core service factors, namely, infrastructure as installed facilities, reliability, promptness, efficiency, and safety are defined.

Qualitative Evaluation by using Intelligent Fuzzy Logical Inference for the Public Education (지능형 퍼지 추론 기법을 적용한 공교육의 정성 평가방법)

  • Kim, Youngtaek
    • The Journal of Korean Association of Computer Education
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    • v.17 no.1
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    • pp.97-105
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    • 2014
  • To enhance the practical usage of solely quantitative evaluation method for each students on the current public education fields which might cause some social problems, an intelligent and adaptive fuzzy logical inference methodology for the additional qualitative evaluation technique is proposed to utilize each students personal characteristic properties to be evaluated. Proposed method uses some verbal descriptions for the linguistic qualifier in addition to the grade points. An imaginary virtual experimentation only has been implemented due to some difficulties with the critical national educational policy problems in the case of some possibly real and practical experimental environments to be utilized for the simulation.

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Development of Fuzzy Inference Mechanism for Intelligent Data and Information Processing (지능적 정보처리를 위한 퍼지추론기관의 구축)

  • 송영배
    • Spatial Information Research
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    • v.7 no.2
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    • pp.191-207
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    • 1999
  • Data and information necessary for solving the spatial decision making problems are imperfect or inaccurate and most are described by natural language. In order to process these arts of information by the computer, the obscure linguistic value need to be described quantitatively to let and computer understand natural language used by humans. For this , the fuzzy set theory and the fuzzy logic are used representative methodology. So this paper describes the construction of the language model by the natural language that user easily can understand and the logical concepts and construction process for building the fuzzy inference mechanism. It makes possible to solve the space related decision making problems intellectually through structuring and inference used by the computer, in case of the evaluation concern or decision making problems are described inaccurate, based on the inaccurate or indistinct data and information.

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Prediction of Transfer Lengths in Pretensioned Concrete Members Using Neuro-Fuzzy System (뉴로-퍼지 시스템을 이용한 프리텐션 콘크리트 부재의 전달길이 예측)

  • Kim, Minsu;Han, Sun-Jin;Cho, Hae-Chang;Oh, Jae-Yuel;Kim, Kang Su
    • Journal of the Korea Concrete Institute
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    • v.28 no.6
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    • pp.723-731
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    • 2016
  • In pretensioned concrete members, a certain bond length from the end of the member is required to secure the effective prestress in the strands, which is defined as the transfer length. However, due to the complex bond mechanism between strands and concrete, most transfer length models based on the deterministic approach have uncertainties and do not provide accurate estimations. Therefore, in this study, Adaptive Neuro-Fuzzy Inference System (ANFIS), a Neuro-Fuzzy System, is introduced to reduce the uncertainties and to estimate the transfer length more accurately in pretensioned concrete member. A total of 253 transfer length test results have been collected from literatures to train ANFIS, and the trained ANFIS algorithm estimated the transfer length very accurately. In addition, a design equation was proposed to calculate the transfer length based on parametric studies and dimensional analyses. Consequently, the proposed equation provided accurate results on the transfer length which are comparable to the ANFIS analysis results.

A note on fuzzy knowledge spaces

  • Jang, Lee-Chae;Kim, Taek-Yun;Jeon, Jong-Duek
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.1
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    • pp.97-101
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    • 2003
  • 최근 수학구조 및 교수-학습과 관련된 연구에 지식공간 이론을 응용하고자하는 논문들이 많이 나오고 있다. 실제로 유의미 학습과 관련된 수행평가와 수학문제를 푸는 능력에 관한 평가를 연구하는데 지식구조가 응용되고 있지만 이를 활용하는데는 많은 애로사항이 있으며 이를 보완하기 위한 여러 가지 방법이 연구되어오고 있다. 특히, Schrepp교수는 스피드문제의 경우로 제한하여 지식공간론을 응용한 일반화된 수학구조의 연구방법을 제시하였다. 본 논문에서는 주관적 지식의 평가를 하게되는 수학구조 및 공간에 관한 연구를 하는데 효과적으로 응용될 수 있는 퍼지지식공간론에 관한 전반적인 기초 이론을 정의하고 그 성질들을 연구하고자한다.

Application of the Fuzzy Set Theory to Analysis of Accident Progression Event Trees with Phenomenological Uncertainty Issues (현상학적 불확실성 인자를 가진 사고진행사건수목의 분석을 위한 퍼지 집합이론의 응용)

  • Ahn, Kwang-Il;Chun, Moon-Hyun
    • Nuclear Engineering and Technology
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    • v.23 no.3
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    • pp.285-298
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    • 1991
  • An example application of the fuzzy set theory is first made to a simple portion of a given accident progression event tree with typical qualitative fuzzy input data, and thereby computational algorithms suitable for application of the fuzzy set theory to the accident progression event tree analysis are identified and illustrated with example applications. Then the procedure used in the simple example is extended to extremely complex accident progression event trees with a number of phenomenological uncertainty issues, i.e., a typical plant damage state‘SEC’of the Zion Nuclear Power Plant risk assessment. The results show that the fuzzy averages of the fuzzy outcomes are very close to the mean values obtained by current methods. The main purpose of this paper is to provide a formal procedure for application of the fuzzy set theory to accident progression event trees with imprecise and qualitative branch probabilities and/or with a number of phenomenological uncertainty issues.

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Household Types and Changes of Work-Family Time Allocation - Adapting Fuzzy-set Ideal Type Analysis - (일-가족 시간배분에 따른 가구유형과 변화 - 퍼지셋 이상형 분석의 적용 -)

  • Kim, Jin-Wook;Choi, Young-Jun
    • Korean Journal of Social Welfare
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    • v.64 no.2
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    • pp.31-54
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    • 2012
  • Along with increasing mothers' employment, work-family reconciliation has been recognised as a key policy agenda in contemporary welfare states. Although various policy instruments have been introduced and expanded in recent years, the problem of time allocation within couples still remains as a fundamental issue, which has been largely underresearched at a micro perspective. In this context, this study aims to identify dominant types of work-family time allocation within married couple, and to apply these types to the Korean case using the fuzzy-set ideal type analysis. Further, a series of multiple regression analyses will be implemented to find factors affecting each ideal type of work-family time allocation. The 1999 and 2009 Korea Time Use Survey datasets will be adopted for the analyses. Married couples are selected as samples only when men work 40 hours or more per week and they have at least one pre-school child. Empirical analyses cover three parts. First of all, four ideal types on work-family time allocation are classified by intersecting two core variables - the ratio of men's (paid) working and family (caring time plus domestic work) time to total working and family time. In this research, the four types will be labelled the traditional male breadwinner model (TM, high working and low family time), the dual burden model (DB, shared working but low family time), the family-friendly male breadwinner model (FM, high working but shared family time), and the adaptive partnership model (AP, shared working and shared family time). By comparing the composition of the four ideal types in 1999 and 2009, it will examine the trend of work-family time allocation in Korea. In addition, multiple regressions will be useful for investigating which characteristics contribute to the different degree of each fuzzy ideal score in the four models. Finally, policy implications and further research agenda will be discussed.

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Elicitation of Collective Intelligence by Fuzzy Relational Methodology (퍼지관계 이론에 의한 집단지성의 도출)

  • Joo, Young-Do
    • Journal of Intelligence and Information Systems
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    • v.17 no.1
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    • pp.17-35
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    • 2011
  • The collective intelligence is a common-based production by the collaboration and competition of many peer individuals. In other words, it is the aggregation of individual intelligence to lead the wisdom of crowd. Recently, the utilization of the collective intelligence has become one of the emerging research areas, since it has been adopted as an important principle of web 2.0 to aim openness, sharing and participation. This paper introduces an approach to seek the collective intelligence by cognition of the relation and interaction among individual participants. It describes a methodology well-suited to evaluate individual intelligence in information retrieval and classification as an application field. The research investigates how to derive and represent such cognitive intelligence from individuals through the application of fuzzy relational theory to personal construct theory and knowledge grid technique. Crucial to this research is to implement formally and process interpretatively the cognitive knowledge of participants who makes the mutual relation and social interaction. What is needed is a technique to analyze cognitive intelligence structure in the form of Hasse diagram, which is an instantiation of this perceptive intelligence of human beings. The search for the collective intelligence requires a theory of similarity to deal with underlying problems; clustering of social subgroups of individuals through identification of individual intelligence and commonality among intelligence and then elicitation of collective intelligence to aggregate the congruence or sharing of all the participants of the entire group. Unlike standard approaches to similarity based on statistical techniques, the method presented employs a theory of fuzzy relational products with the related computational procedures to cover issues of similarity and dissimilarity.