• 제목/요약/키워드: a priori

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Segmentation of Cooperatives' Mutuality Bank for Effective Risk Management using Factor Analysis and Cluster Analysis

  • Cho, Yong-Jun;Ko, Seoung-Gon
    • Journal of the Korean Data and Information Science Society
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    • 제19권3호
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    • pp.831-844
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    • 2008
  • Since cooperatives consist of many distinct members in the management environment and characteristics, it is necessary to make similar cooperatives into a few groups for the effective risk management of cooperatives' mutuality bank. This paper is a priori research for suggesting a guidance for effective risk management of cooperatives with different management strategy. For such purpose, we propose a way to group the members of cooperative's mutuality bank. The 30 continuous variables which is relative to cooperatives' management status are considered and six factors are extracted from those variables through factor analysis with empirical consideration to avoid wrong grouping and to enhance the practical interpretation. Based on extracted six factors and additional 3 categorical variables, six representative groups are derived by the two step clustering analysis. These findings are useful to execute a discriminatory risk management and other management strategy for a mutuality bank and others.

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NUMERICAL DISCRETIZATION OF A POPULATION DIFFUSION EQUATION

  • Cho, Sung-Min;Kim, Dong-Ho;Kim, Mi-Young;Park, Eun-Jae
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제14권3호
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    • pp.189-200
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    • 2010
  • A numerical method is proposed and analyzed to approximate a mathematical model of age-dependent population dynamics with spatial diffusion. The model takes a form of nonlinear and nonlocal system of integro-differential equations. A finite difference method along the characteristic age-time direction is considered and primal mixed finite elements are used in the spatial variable. A priori error estimates are derived for the relevant variables.

A Direct Integration Approach for the Estimation of Time-Dependent Boundary Heat Flux

  • Kim, Sin;Kim, Min-Chan;Kim, Kyung-Youn
    • Journal of Mechanical Science and Technology
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    • 제16권10호
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    • pp.1320-1326
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    • 2002
  • In a one-dimensional heat conduction domain with heated and insulated walls, an integral approach is proposed to estimate time-dependent boundary heat flux without internal measurements. It is assumed that the expression of the heat flux is not known a priori. Hence, the present inverse heat conduction problem is classified as a function estimation problem. The spatial temperature distribution is approximated as a third-order polynomial of position, whose four coefficients are determined from the heat fluxes and the temperatures at both ends at each measurement. After integrating the heat conduction equation over spatial and time domain, respectively, a simple and non-iterative recursive equation to estimate the time-dependent boundary heat flux is derived. Several examples are introduced to show the effectiveness of the present approach.

A neural network approach for simulating stationary stochastic processes

  • Beer, Michael;Spanos, Pol D.
    • Structural Engineering and Mechanics
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    • 제32권1호
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    • pp.71-94
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    • 2009
  • In this paper a procedure for Monte Carlo simulation of univariate stationary stochastic processes with the aid of neural networks is presented. Neural networks operate model-free and, thus, circumvent the need of specifying a priori statistical properties of the process, as needed traditionally. This is particularly advantageous when only limited data are available. A neural network can capture the "pattern" of a short observed time series. Afterwards, it can directly generate stochastic process realizations which capture the properties of the underlying data. In the present study a simple feed-forward network with focused time-memory is utilized. The proposed procedure is demonstrated by examples of Monte Carlo simulation, by synthesis of future values of an initially short single process record.

유전 알고리즘기반 퍼지 모델을 이용한 모터 고장 진단 자동화 시스템의 구현 (Implementation of Automated Motor Fault Diagnosis System Using GA-based Fuzzy Model)

  • 박태근;곽기석;윤태성;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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    • pp.24-26
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    • 2005
  • At present, KS-1000 which is one of a commercial measurement instrument for motor fault diagnosis has been used in industrial field. The measurement system of KS-1000 is composed of three part : harmonic acquisition, signal processing by KS-1000 algorithm, diagnosis for motor fault. First of all, voltage signal taken from harmonic sensor is analysed for frequency by KS-1000 algorithm. Then, based on the result values of analysis skilled expert makes a judgment about whether motor system is the abnormality or degradation state. But the expert system such a motor fault diagnosis is very difficult to bring the expectable results by mathematical modeling due to the complexity of judgment process. In this reason, we propose an automation system using fuzzy model based on genetic algorithm(GA) that builded a qualitative model of a system without priori knowledge about a system provided numerical input output data.

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시간지연 시스템에서의 불확실성 추정을 갖는 슬라이딩 모드제어 (Sliding Mode Control with Uncertainty Adaptation for Uncertain Input-Delay Systems)

  • 노영훈;오준호
    • 제어로봇시스템학회논문지
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    • 제6권11호
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    • pp.963-967
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    • 2000
  • This paper deals with a sliding mode control with uncertainty adaptation for the robust stabilization of input-delay systems with unknown uncertainties. A sliding surface including a state predictor is employed to compensate for the effect of the input delay. The proposed method does not need a priori knowledge of upper bounds on the norm of uncertainties, but estimates those upper bounds by adaptation laws based on the sliding surface. Then, a robust control law with the uncertainty adaptation is derived to ensure the existence of the sliding mode. A numerical example is given to illustrate the design procedure.

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적응 법칙 기반의 퍼지 기초 함수를 이용한 도립진자의 마찰력 관측기 설계 및 마찰력 보상 (An Observer Design and Compensation of the Friction in an Inverted Pendulum using Adaptive Fuzzy Basis Functions Expansion)

  • 박덕기;박민호;좌동경;홍석교
    • 제어로봇시스템학회논문지
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    • 제13권4호
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    • pp.335-343
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    • 2007
  • This paper deals with the method to estimate the friction in a system. We study a nonlinear friction model to estimate the friction in an inverted pendulum and approximate the friction model using fuzzy basis functions expansion. To demonstrate the friction observer using FBFs, we derive a update rule based on the error term that is formed by the output from a real system and observer output with a friction estimate. And two compensation algorithms to improve the response of an inverted pendulum are proposed. The first method that a observer parameter is updated in on-line and the friction is compensated at the same time. The second method is to compensate the friction with observer parameter estimated priori. The two methods is compared through the experimental results.

뉴로-퍼지 알고리듬을 이용한 얼굴인식 (Face Recognition Using a Neuro-Fuzzy Algorithm)

  • 이상영;함영국;박래홍
    • 전자공학회논문지B
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    • 제32B권1호
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    • pp.50-63
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    • 1995
  • In this paper, we propose a face recognition method using a neuro-fuzzy algorithm. In the preprocessing step, we extract the face part from the background image by tracking face boundaries. Then based on the a priori knowledge of human faces we extract the features such as widths of eyes and mouth, and distances from eye to nose and nose to mouth. In the recognition step. We use a neuro-fuzzy algorithm that employs a fuzzy membership function and modified error backpropagation algorithm. The former absorbs the variation of feature values and the latter shows good learning efficiency. Computer simulation results with 20 persons show that the proposed method gives higher recognition rate than the conventional ones.

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Convex polytope을 이용한 퍼지 클러스터링 (Fuzzy clustering involving convex polytope)

  • 김재현;서일홍;이정훈
    • 전자공학회논문지C
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    • 제34C권7호
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    • pp.51-60
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    • 1997
  • Prototype based methods are commonly used in cluster analysis and the results may be highly dependent on the prototype used. In this paper, we propose a fuzzy clustering method that involves adaptively expanding convex polytopes. Thus, the dependency on the use of prototypes can be eliminated. The proposed method makes it possible to effectively represent an arbitrarily distributed data set without a priori knowledge of the number of clusters in the data set. Specifically, nonlinear membership functions are utilized to determine whether a new cluster is created or which vertex of the cluster should be expanded. For this, the membership function of a new vertex is assigned according to not only a distance measure between an incoming pattern vector and a current vertex, but also the amount how much the current vertex has been modified. Therefore, cluster expansion can be only allowed for one cluster per incoming pattern. Several experimental results are given to show the validity of our mehtod.

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전자부품 조립공정의 자동화를 \ulcorner나 실시간 영상처리 알고리즘에 관한 연구 (A Real-Time Image Processing Algorithms for An Automatic Assembly System of Electronic Components)

  • 유범재;오영석;오상록
    • 대한전기학회논문지
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    • 제37권11호
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    • pp.804-815
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    • 1988
  • Real-time image processing algorithms to detect position and orientation of rectangular type electronic components are developed. The position detection algorithm is implemented with the use of projection method which is insensitive to noise. Also dynamic thresholding method of projection is employed in order to distinguish between the boundary of a component and any marking on the component. The orientation is determined by Hough transform of boundary candidates of a component, which is obtained a priori by a simple edge detection method. For real-time processing of both position and orientation for a component which is not aligned well, parallel processing method of image data is proposed and tested in real-time.

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