• 제목/요약/키워드: Fuzzy transformation

검색결과 103건 처리시간 0.029초

SUMS AND JOINS OF T-FUZZY TRANSFORMATION SEMIGROUPS

  • Cho, Sung-Jin;Kim, Jae-Gyeom
    • Journal of applied mathematics & informatics
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    • 제8권1호
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    • pp.273-283
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    • 2001
  • We introduce sums and joins of T-fuzzy transformation semi-groups and investigate their algebraic structures.

The Rank Transform Method in Nonparametric Fuzzy Regression Model

  • Choi, Seung-Hoe;Lee, Myung-Sook
    • Journal of the Korean Data and Information Science Society
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    • 제15권3호
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    • pp.617-624
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    • 2004
  • In this article the fuzzy number rank and the fuzzy rank transformation method are introduced in order to analyse the non-parametric fuzzy regression model which cannot be described as a specific functional form such as the crisp data and fuzzy data as a independent and dependent variables respectively. The effectiveness of fuzzy rank transformation methods is compared with other methods through the numerical examples.

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New Fuzzy Inference System Using a Kernel-based Method

  • Kim, Jong-Cheol;Won, Sang-Chul;Suga, Yasuo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.2393-2398
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    • 2003
  • In this paper, we proposes a new fuzzy inference system for modeling nonlinear systems given input and output data. In the suggested fuzzy inference system, the number of fuzzy rules and parameter values of membership functions are automatically decided by using the kernel-based method. The kernel-based method individually performs linear transformation and kernel mapping. Linear transformation projects input space into linearly transformed input space. Kernel mapping projects linearly transformed input space into high dimensional feature space. The structure of the proposed fuzzy inference system is equal to a Takagi-Sugeno fuzzy model whose input variables are weighted linear combinations of input variables. In addition, the number of fuzzy rules can be reduced under the condition of optimizing a given criterion by adjusting linear transformation matrix and parameter values of kernel functions using the gradient descent method. Once a structure is selected, coefficients in consequent part are determined by the least square method. Simulated result illustrates the effectiveness of the proposed technique.

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Correlation Test by Reduced-Spread of Fuzzy Variance

  • Kang, Man-Ki
    • Communications for Statistical Applications and Methods
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    • 제19권1호
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    • pp.147-155
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    • 2012
  • We propose some properties for a fuzzy correlation test by reduced-spread fuzzy variance for sample fuzzy data. First, we define the condition of fuzzy data for repeatedly observed data or that which includes error term data. By using the average of spreads for fuzzy numbers, we reduce the spread of fuzzy variance and define the agreement index for the degree of acceptance and rejection. Given a non-normal random fuzzy sample, we have bivariate normal distribution by apply Box-Cox power fuzzy transformation and test the fuzzy correlation for independence between the variables provided by the agreement index.

Invariant Range Image Multi-Pose Face Recognition Using Fuzzy c-Means

  • Phokharatkul, Pisit;Pansang, Seri
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1244-1248
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    • 2005
  • In this paper, we propose fuzzy c-means (FCM) to solve recognition errors in invariant range image, multi-pose face recognition. Scale, center and pose error problems were solved using geometric transformation. Range image face data was digitized into range image data by using the laser range finder that does not depend on the ambient light source. Then, the digitized range image face data is used as a model to generate multi-pose data. Each pose data size was reduced by linear reduction into the database. The reduced range image face data was transformed to the gradient face model for facial feature image extraction and also for matching using the fuzzy membership adjusted by fuzzy c-means. The proposed method was tested using facial range images from 40 people with normal facial expressions. The output of the detection and recognition system has to be accurate to about 93 percent. Simultaneously, the system must be robust enough to overcome typical image-acquisition problems such as noise, vertical rotated face and range resolution.

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분포무관추정량을 이용한 퍼지회귀모형 (Fuzzy Linear Regression Using Distribution Free Method)

  • 윤진희;최승회
    • Communications for Statistical Applications and Methods
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    • 제16권5호
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    • pp.781-790
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    • 2009
  • 본 논문에서는 퍼지수를 포함한 모수적 회귀모형을 추정하기 위하여 분포무관추정량으로 알려진 순위 변환방법과 Theil 방법을 소개한다. 순위 변환방법은 퍼지수의 ${\alpha}$-수준집합의 중심과 폭에 대한 순위를 이용하고 Theil 방법은 ${\alpha}$-수준집합의 중심과 폭에 대한 추정한 값들의 중위수를 이용한다. 예제를 이용하여 분포무관추정량으로 추정된 퍼지회귀모형의 효율성을 최소자승법과 여러 가지 방법으로 추정된 퍼지회귀모형과 비교한다.

Fuzzy modeling using transformed input space partitioning

  • You, Je-Young;Lee, Sang-Chul;Won, Sang-Chul
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.494-498
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    • 1996
  • Three fuzzy input space partitoining methods, which are grid, tree, and scatter method, are mainly used until now. These partition methods represent good performance in the modeling of the linear system and nonlinear system with independent modeling variables. But in the case of the nonlinear system with the coupled modeling variables, there should be many fuzzy rules for acquiring the exact fuzzy model. In this paper, it shows that the fuzzy model is acquired using transformed modeling vector by linear transformation of the modeling vector.

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퍼지 집합 이론을 이용한 공급지장 기대치의 산정 (LOLE(Loss of Load Expctatiom) Evaluation using Fuzzy Set Theory)

  • 심재홍;정현수;김진오
    • 대한전기학회논문지:전력기술부문A
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    • 제48권9호
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    • pp.1055-1063
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    • 1999
  • This paper present a conceptual possibilistic approach using fuzzy set theory to manage the uncertainties in the given reliability input date of the practical power system. In this paper, an algorithm is introduced to calculate the possibilstic reliability indices according to the degree of uncertainty in the given data. The probability distribution function can be transformed into an appropriate possibilstic representation using the probability-Possibility Consistency principle(PPCP) algorithm. In this the algorithm, the transformation is performation by making a compromise between the transformation consistency and the human updating experience. Fuzzy classifcation theory is applied to reduced the number of load data. The fuzzy classification method determines the closeness of load data points by assigning them to various clusters and then determening the distance between the clusters. The IEEE-RTS with 32-generating units is used to demonstrate the capability of the proposed algorithm.

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Several decompositions of fuzzy transformation semigroups

  • Cho, Sung-Jin;Kim, Han-Doo
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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    • pp.25-28
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    • 2001
  • We introduce sums and joins of fuzzy finite state machines and investigate their algebraic structures.

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퍼지DEA에 의한 항만의 효율성 및 순위 측정방법: 평균지수변환모형 접근 (A Measurement Way of Seaport Efficiency and Ranking Using Fuzzy DEA: Average Index Transformation Model Approach)

  • 박노경
    • 한국항만경제학회지
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    • 제26권2호
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    • pp.82-98
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    • 2010
  • 본 연구에서는 첫째, 퍼지DEA모형을 해운항만분야에 이용한 국내외 기존연구들을 간략하게 검토하였으며, 둘째, Campos and Gonzalez(1989), 임성묵(2008)의 평균지수변환모형을 이론적으로 소개하였으며, 셋째, 국내 26개항만을 대상으로 2개의 투입요소(접안능력, 하역능력), 2개의 산출요소(화물처리량, 입출항척수)를 이용하여 평균지수변환모형에 의거하여 효율성을 분석하고 해석하였다. 실증분석결과를 요약해 보면 다음과 같다. 첫째, 일반 투입지향 CCR모형에서는 통영, 고현, 옥포, 속초항이 효율적이었으며, 여수항이 90% 후반의 효율성을 보였다. 둘째, 퍼지DEA 평균지수변환모형에서는 고현, 속초항이 가장 효율적이었으며, 옥포, 여수항은 람다값이 커질수록 효율성이 증가되었다. 또한 완도, 여수, 서귀포항은 람다값이 높아질 수록 효율성수치도 높아졌다. 셋째, 일반적인 투입지향 CCR 모형의 효율성 수치와 평균지수변환법에 의한 효율성수치의 평균순위는 거의 일치하였다. 본 논문이 갖는 정책적인 함의는 국내항만의 정책입안담당자들은 투입요소와 산출요소의 값을 정확히 알지 못하고 애매모호한 수준에서 알고 있을 때, 본 논문에서 사용한 퍼지 DEA 평균지수모형을 이용할 필요성이 있다는 점이다.