• 제목/요약/키워드: Error function

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적응 유한 요소법을 위한 2차 형상 함수 오차 추정 (A Simple Posteriori Error Estimate Method For Adaptive Finite Element Mesh Generation Using Quadratic Shape Funtion)

  • 김형석;최홍순;최경;한송엽
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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    • pp.87-90
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    • 1988
  • This paper reports a simple posteriori error estimate method for adaptive finite element mesh generation using quadratic shape function especially for the magnetic field problems. The elements of quadratic shape function have more precise solution than those of linear shape function. Therefore, the difference of two solutions gives error quantity. The method uses the magnetic flux density error as a basis for refinement. This estimator is tested on two dimensional problem which has singular points. The estimated error is always under estimated but in same order as exact error, and this method is much simpler and more convenient than other methods. The result shows that the adaptive mesh gives even better rate of convergence in global error than the uniform mesh.

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Error propagation effects for explicit pseudodynamic algorithms

  • Chang, Shuenn-Yih
    • Structural Engineering and Mechanics
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    • 제10권2호
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    • pp.157-164
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    • 2000
  • This paper discusses the error propagation characteristics of the Newmark explicit method, modified Newmark explicit method and ${\alpha}$-function dissipative explicit method in pseudodynamic tests. The Newmark explicit method is non-dissipative while the ${\alpha}$-function dissipative explicit method and the modified Newmark explicit method are dissipative and can eliminate the spurious participation of high frequency responses. In addition, error propagation analysis shows that the modified Newmark explicit method and the ${\alpha}$-function dissipative explicit method possess much better error propagation properties when compared to the Newmark explicit method. The major disadvantages of the modified Newmark explicit method are the positive lower stability limit and undesired numerical dissipation. Thus, the ${\alpha}$-function dissipative explicit method might be the most appropriate explicit pseudodynamic algorithm.

계측기에서 얻어진 주파수 응답 함수의 오차 제거 방안 - 전달함수 합성법에의 응용 - (A Suggestion of Method to Remove Bias Error of the FRF Obtained by FFT Analyzer - Application of TFS -)

  • 김승엽;정의봉;서영수
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2003년도 춘계학술대회논문집
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    • pp.408-413
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    • 2003
  • The frequency response function(FRF) of each substructure is used for the transfer function synthesis method(TFS). The dynamic characteristics of the full system are obtained by synthesizing FRFs of each substructure. The validation of TFS depends on accuracy for FRF of each substructure. Impact hammer testing Is widely used to obtain the modal characteristics of structures However. the FRF obtained from impact hammer testing contains bias errors, such as finite record length error and leakage error of which characteristic depends on data acquisition time which we call record length. In this paper, a method to remove hose errors is proposed so as to enhance results of TFS. Numerical and experimental examples show that the FRF of full structure can be predicted nearly exactly by the method proposed in this paper.

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Membership Function-based Classification Algorithms for Stability improvements of BCI Systems

  • Yeom, Hong-Gi;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제10권1호
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    • pp.59-64
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    • 2010
  • To improve system performance, we apply the concept of membership function to Variance Considered Machines (VCMs) which is a modified algorithm of Support Vector Machines (SVMs) proposed in our previous studies. Many classification algorithms separate nonlinear data well. However, existing algorithms have ignored the fact that probabilities of error are very high in the data-mixed area. Therefore, we make our algorithm ignore data which has high error probabilities and consider data importantly which has low error probabilities to generate system output according to the probabilities of error. To get membership function, we calculate sigmoid function from the dataset by considering means and variances. After computation, this membership function is applied to the VCMs.

A Non-Linear Exponential(NLINEX) Loss Function in Bayesian Analysis

  • Islam, A.F.M.Saiful;Roy, M.K.;Ali, M.Masoom
    • Journal of the Korean Data and Information Science Society
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    • 제15권4호
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    • pp.899-910
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    • 2004
  • In this paper we have proposed a new loss function, namely, non-linear exponential(NLINEX) loss function, which is quite asymmetric in nature. We obtained the Bayes estimator under exponential(LINEX) and squared error(SE) loss functions. Moreover, a numerical comparison among the Bayes estimators of power function distribution under SE, LINEX, and NLINEX loss function have been made.

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라이시안 감쇄 채널에서의 위상오류 분포 (On the Distribution of Phase Error in the Rician Fading Channel)

  • 김민종;한영열
    • 한국전자파학회논문지
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    • 제13권8호
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    • pp.797-803
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    • 2002
  • 본 논문에서는 라이시안(Rician) 감쇄가 존재하는 채널 환경에서 협대역 잡음이 더하여진 경우에 대역 여파기를 통과한 수신신호의 위상오류에 대한 확률 밀도 함수를 유도하고 0차 모먼트가 1이 됨을 보임으로써 확률밀도 함수로서의 타당성을 검증한다. 일반적으로 감쇄 환경에서 시스템의 오류 확률은 먼저 가산성 백색 가우시안 잡음(AWGN : Additive White Gaussian Noise)만이 존재할 때의 오류 확률을 구한 후, 그 결과 식을 해당 감쇄에 대한 확률 밀도 함수로 평균을 취하여 구한다. 하지만 본 논문에서는 감쇄 환경에서의 수신 신호에 대한 위상 오류식을 구한 다음, 그 식을 한번의 이중 적분을 취함으로써 오류 확률을 구하게 된다.

Improving the Error Back-Propagation Algorithm for Imbalanced Data Sets

  • Oh, Sang-Hoon
    • International Journal of Contents
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    • 제8권2호
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    • pp.7-12
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    • 2012
  • Imbalanced data sets are difficult to be classified since most classifiers are developed based on the assumption that class distributions are well-balanced. In order to improve the error back-propagation algorithm for the classification of imbalanced data sets, a new error function is proposed. The error function controls weight-updating with regards to the classes in which the training samples are. This has the effect that samples in the minority class have a greater chance to be classified but samples in the majority class have a less chance to be classified. The proposed method is compared with the two-phase, threshold-moving, and target node methods through simulations in a mammography data set and the proposed method attains the best results.

DOMAIN BLOCK ESTIMATING FUNCTION FOR FRACTAL IMAGE CODING

  • Kousuke-Imamura;Yuuji-Tanaka;Hideo-Kuroda
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1999년도 KOBA 방송기술 워크샵 KOBA Broadcasting Technology Workshop
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    • pp.57.2-62
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    • 1999
  • Fractal coding is image compression techniques using one of image characteristics self-transformability. In fractal image coding, the encoding process is to select the domain block similar to a range block. The reconstructed image quality of fractal image coding depends on similitude between a range block and the selected domain block. Domain block similar to a range blocks. In fact, the error of the reconstructed image adds up the generated error in encoding process and the generated error in decoding process. But current domain block estimating function considered only the encoding error. We propose a domain block estimating function to consider not only the encoding error but also the decoding error. By computer simulation, it was verified to obtain the high quality reconstructed image.

원자력발전소 비상운전시의 운전원 인지오류 예측 지원체계의 개발 (A Framework for the Support of Predictive Cognitive Error Analysis of Emergency Tasks in Nuclear Power Plants)

  • 김재환;정원대
    • 한국안전학회지
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    • 제16권3호
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    • pp.117-124
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    • 2001
  • This paper introduces m analysis framework and procedure for the support of the cognitive error analysis of emergency tasks in nuclear poler plants. The framework provides a new perspective in the utilization of influencing factors into error prediction. The framework can be characterized by two features. First, influencing factors that affect the occurrence of human error me classified into three groups, i.e., task characteristic factors(TCF), situation factors(SF), and performance assisting factors(PAF). This classification aims to support error prediction from the viewpoint of assessing the adequacy of PAF under given TCF and SF. Second, the assessment of influencing factors is made by each cognitive function. Through this, influencing factors assessment and error prediction can be made in an integrative way according to each cognitive function. In addition, it helps analysts identify vulnerable cognitive functions and error factors, and obtain specific nor reduction strategies. The proposed framework was applied to the error analysis of the bleed and feed operation of nuclear emergency tasks.

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