• 한국환경과학회지
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• 제22권8호
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• 한국해안해양공학회지
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• 제6권1호
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• pp.88-93
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• 1994

유한수심에서의 불규칙파에 적용할 수 있는 파고의 확률분포함수를 2가지 해석적 방법으로 유도하였다. 첫번째 방법으로 새로이 유도된 확률분포함수는 Rayleigh 확률분포함수에 대한 직교 다항식을 유도함으로써 급수형태로 표시된다. 유도된 확률밀도함수를 비정규성이 강한 천해에서 측정한 파랑자료와 비교하였다. 확률밀도함수가 자료의 막대그래프와 잘 일치하였으나, 확률밀도함수가 급수로 표시되어 있기 때문에 파고가 큰 부분에서 음의 확률값이 된다. 비록 음의 확률값의 크기가 작다 하더라도 파고의 극치분포함수를 구하기에 부적절하다고 판단된다. 두번째 방법은 최대 엔트로피 법(maximum entropy method)을 적용하여 파고 분포와 매우 잘 일치하며, 극치파고분포와 파고의 통계적인 특성 등을 추정하는 데 매우 유용함을 알 수 있다. 그러나 최대 엔트로피 법을 사용했을 경우, 비정규분포 특성을 나타내는 변위의 분포함수와 파고의 분포함수 사이의 함수관계를 구할 수 없었다.

• 대한금속재료학회지
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• 제46권9호
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• pp.554-562
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• 2008

The distribution and prediction interval for the misorientation angle of grain boundary at which $Cr_2N$ was precipitated during heating at $900^{\circ}C$ for $10^4$ sec were newly estimated, and followed by the estimation of mathematical and median rank methods. The probability density function of the misorientation angle can be estimated by a statistical analysis. And then the ($1-{\alpha}$)100% prediction interval of misorientation angle obtained by the estimated probability density function. If the estimated probability density function was symmetric then a prediction interval for the misorientation angle could be derived by the estimated probability density function. In the case of non-symmetric probability density function, the prediction interval could be obtained from the cumulative distribution function of the estimated probability density function. In this paper, 95, 99 and 99.73% prediction interval obtained by probability density function method and cumulative distribution function method and compared with the former results by median rank regression or mathematical method.

• 대한수학교육학회지:학교수학
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• 제4권4호
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• pp.677-688
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• 2002

The context and intuitive understanding is very important in Statistics Education. Especially, there is a need to mitigate student's difficulty in studying probability density function. One of teaching method this concept is to using relative frequency histogram. But, as using this method, we should know several problems included in that. This study investigate problems in the method for teaching probability density function as gradual meaning of histogram. Also, as alternative approach, this thesis introduce the density curve concept. The application of four methods to teach the concept of the probability density function and analysis of the survey result is done in this research.

• Structural Engineering and Mechanics
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• 제86권3호
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• pp.349-359
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• 2023

This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.49.1-49
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• 2001

The skin color model is a very important concept in face detection, face recognition and face tracking. Usually, this model is obtained by estimating a probability density function of skin color distribution. In many cases, it is assumed that the underlying density function follows a Gaussian distribution. In this paper, a new method for non-parametric estimation of the probability density function, by using feed-forward neural network, is used to estimate the underlying skin color model. By using this method, the resulting skin color model is better than the Gaussian estimation and substantially approaches the real distribution. Applications to face detection and face ...

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제5B권3호
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• pp.258-261
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• 2005

The Preisach model needs a distribution function or Everett function to simulate the hysteresis phenomena. To obtain these functions, many experimental data obtained from the first order transition curves are usually required. In this paper, a simple procedure to determine the Preisach density function using the Gaussian distribution function and genetic algorithm is proposed. The Preisach density function for the interaction field axis is known to have Gaussian distribution. To determine the density and distribution, genetic algorithm is adopted to decide the Gaussian parameters. With this method, just basic data like the initial magnetization curve or saturation curves are enough to get the agreeable density function. The results are compared with experimental data and we got good agreements comparing the simulation results with the experiment ones.

• 정보처리학회논문지B
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• 제13B권1호
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• pp.27-34
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• 2006

본 연구에서는 엔트로피를 이용한 독립성분분석(ICA : Independent Component Analysis)에서 점수함수(score function)를 생성하는 알고리즘을 제안한다. 점수함수를 생성하기 위해서 원 신호(original signals)에 대한 확률밀도함수의 추정이 반드시 필요하고 밀도함수가 미분 가능해야 한다. 따라서 원 신호에 따른 적응적인 점수 함수를 유도할 수 있도록 커널 기반의 밀도추정(kernel density estimation)방법을 사용하였으며, 보다 빠른 밀도 추정 계산을 위해서 식의 형태를 컨볼루션(convolution) 변환 한 후, 컨볼루션을 빠르게 계산할 수 있는 FFT(Fast Fourier Transform) 알고리즘을 이용하였다. 제안한 점수함수 생성 방법은 원 신호에 확률밀도분포와 추정된 신호의 확률밀도 분포의 오차를 줄이는 역할을 한다 실험 결과, 암묵신호분리(blind source separation)문제에서 기존의 Extended Infomax 알고리즘과 Fixed Point ICA 보다 원 신호와 유사한 밀도함수를 추정하였고, 분리된 신호의 신호대잡음비등(SNR)에 있어서 향상된 성능을 얻을 수 있었다.

• Structural Engineering and Mechanics
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• 제68권1호
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• pp.39-51
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• 2018

In this study, a frequency domain model updating method is presented using power spectral density (PSD) data. It uses the sensitivity of PSD function with respect to the unknown structural parameters through a decomposed form of transfer function. The stiffness parameters are captured with high accuracy through solving the sensitivity equations utilizing the least square approach. Using numerically noise polluted data, the model updating results of a truss model prove robustness of the method against measurement and mass modelling errors. Results prove the capabilities of the method for parameter estimation using highly noise polluted data of low ranges of excitation frequency.

• Journal of Mechanical Science and Technology
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• 제17권10호
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• pp.1496-1506
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• 2003

The SIMP (solid isotropic material with penalization) approach is perhaps the most popular density variable relaxation method in topology optimization. This method has been very successful in many applications, but the optimization solution convergence can be improved when new variables, not the direct density variables, are used as the design variables. In this work, we newly propose S-shape functions mapping the original density variables nonlinearly to new design variables. The main role of S-shape function is to push intermediate densities to either lower or upper bounds. In particular, this method works well with nonlinear mathematical programming methods. A method of feasible directions is chosen as a nonlinear mathematical programming method in order to show the effects of the S-shape scaling function on the solution convergence.