• 한국방재안전학회논문집
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• 제6권2호
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• pp.1-8
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• 2013

우리나라 전체 재해 60%이상인 태풍과 같은 바람재난으로부터 구조물이나 외장재가 안전과 사용성 측면에서 설계되려면 내풍설계과정에서 기본풍속, 설계속도압, 풍하중 등 많은 파라미터들이 요구된다. 본 논문에서는 최근 2003년부터 2012년까지의 10년 동안 년최대풍속이 발생한 날의 풍속으로부터 확률과정과 확률분포, 통계적 성질 등을 알아보기 위하여 8개의 대표지점을 여수, 인천, 서울, 청주, 원주, 대구, 속초, 울릉도로 선정했다. 선정된 각 지점에 대한 최근 10년 동안의 풍속자료는 기상청으로부터 획득했다. 각 지점의 획득한 풍속자료는 우리나라를 직접 통과하면서 영향을 미친 태풍과 통과는 안했지만 간접 영향을 미친 태풍, 년최대순간풍속과 년최대평균퐁속이 같은 날 등을 고려 90개의 앙상블 중 선별된 33개의 모집단에 대한 풍속자료의 확률과정 및 확률분포의 특성을 비교 검토하였다.

• Ocean Systems Engineering
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• 제4권4호
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• pp.293-308
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• 2014

Unlike the traditional displacement type vessels, the high speed planing crafts are supported by the lift forces which are highly non-linear. This non-linear phenomenon causes their motions in an irregular seaway to be non-Gaussian. In general, it may not be possible to express the probability distribution of such processes by an analytical formula. Also the process might not be stationary or ergodic in which case the statistical behavior of the motion to be constantly changing with time. Therefore the extreme values of such a process can no longer be calculated using the analytical formulae applicable to Gaussian processes. Since closed form analytical solutions do not exist, recourse is taken to fitting a distribution to the data and estimating the statistical properties of the process from this fitted probability distribution. The peaks over threshold analysis and fitting of the Generalized Pareto Distribution are explored in this paper as an alternative to Weibull, Generalized Gamma and Rayleigh distributions in predicting the short term extreme value of a random process.

• Communications for Statistical Applications and Methods
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• 제22권3호
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• pp.277-283
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• 2015

Pickands constant $H_{\alpha}$ appears in the classical result about tail probabilities of the extremes of Gaussian processes and there exist several different representations of Pickands constant. However, the exact value of $H_{\alpha}$ is unknown except for two special Gaussian processes. Significant effort has been made to find numerical approximations of $H_{\alpha}$. In this paper, we attempt to compute numerically $H_{\alpha}$ based on its representation derived by $H{\ddot{u}}sler$ (1999) and Albin and Choi (2010). Our estimates are compared with the often quoted conjecture $H_{\alpha}=1/{\Gamma}(1/{\alpha})$ for 0 < ${\alpha}$ ${\leq}$ 2. This conjecture does not seem compatible with our simulation result for 1 < ${\alpha}$ < 2, which is also recently observed by Dieker and Yakir (2014) who devised a reliable algorithm to estimate these constants along with a detailed error analysis.

• 한국습지학회지
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• 제11권1호
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• pp.49-64
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• 2009

홍수나 가뭄 등 극한 사상을 예측하여 재해에 대비하거나 또는 수자원을 효율적으로 관리, 배분하기 위하여 강우-유출 모형이 이용되고 있다. 그러나 많은 수문학자들은 강우-유출 모형이 가질 수밖에 없는 불확실성에 대하여 언급하였다. 실제 유역에 내린 강우는 증발과 증산, 차단, 침투 등 여러 과정을 거쳐 유출로 이어지는데, 모형에서는 이러한 복잡한 물리적 과정을 단순화하여 표현하였으므로 불확실성이 반드시 존재할 수밖에 없는 것이다. 따라서 모형으로부터의 모의 결과를 신뢰할 수 있는지를 정량적으로 판단하는 과정이 이루어져야 한다. 본 논문에서는 현재까지 강우-유출 모형의 불확실성을 평가한 선행 연구 중 Montanari와 Brath(2004)가 제시한 Meta-Gaussian 기법을 이용하여 강우-유출 모형 모의 결과에 대한 불확실성을 검토하였다. 이 기법은 모형 오차의 확률 분포형으로부터 신뢰구간의 상한계와 하한계를 추정하는 방법으로 수문모형의 전역적 불확실성(Global Uncertainty)을 정량화할 수 있다. 본 논문에서는 동일한 강우사상에 대한 물리적 기반의 분포형 모형인 $Vflo^{TM}$ 모형과 개념적 준 분포형 모형인 HEC-HMS 모형으로부터 모의된 유출량을 Meta-Gaussian 기법을 적용하여 불확실성을 분석하였다.

• 충청수학회지
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• 제5권1호
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• pp.23-34
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• 1992

This is an extension of results of Wiener's nonlinear noise theory from noises generated by the Wiener process to noises generated by processes with stationary Gaussian increments. In particular, using Nisio's Approach, we show that every measurable ergodic noise can be approximated in law by Gaussian process-presentable noise.

• East Asian mathematical journal
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• 제24권3호
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• pp.275-287
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• 2008

In this paper, using large deviation results for Gaussian processes, we establish some functional limit theorems for increments of a fractional Brownian motion in the usual sup-norm via estimating large deviation probabilities for increments of a fractional Brownian motion.

• 대한수학회보
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• 제35권2호
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• pp.209-225
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• 1998

In this paper we obtain sharp upper and lower bounds of small ball oprobabilities for Gaussian processes with stationary increments, whose results are essential to estabilish Chung type laws of iterated logarithm.

• Wind and Structures
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• 제23권4호
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• pp.275-300
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• 2016

Synchronous multi-pressure measurements were carried out with relatively long time duration for a double-layer reticulated shell roof model in the atmospheric boundary layer wind tunnel. Since the long roof is open at two ends for the storage of coal piles, three different testing cases were considered as the empty roof without coal piles (Case A), half coal piles inside (Case B) and full coal piles inside (Case C). Based on the wind tunnel test results, non-Gaussian time-dependent statistics of net wind pressure on the shell roof were quantified in terms of skewness and kurtosis. It was found that the direct statistical estimation of high-order moments and peak factors is quite sensitive to the duration of wind pressure time-history data. The maximum value of COVs (Coefficients of variations) of high-order moments is up to 1.05 for several measured pressure processes. The Mixture distribution models are proposed for better modeling the distribution of a parent pressure process. With the aid of mixture parent distribution models, the existing translated-peak-process (TPP) method has been revised and improved in the estimation of non-Gaussian peak factors. Finally, non-Gaussian peak factors of wind pressure, particularly for those observed hardening pressure process, were calculated by employing various state-of-the-art methods and compared to the direct statistical analysis of the measured long-duration wind pressure data. The estimated non-Gaussian peak factors for a hardening pressure process at the leading edge of the roof were varying from 3.6229, 3.3693 to 3.3416 corresponding to three different cases of A, B and C.

• Journal of Information Processing Systems
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• 제14권2호
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• pp.539-551
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• 2018

Images are unavoidably contaminated with different types of noise during the processes of image acquisition and transmission. The main forms of noise are impulse noise (is also called salt and pepper noise) and Gaussian noise. In this paper, an effective method of removing mixed noise from images is proposed. In general, different types of denoising methods are designed for different types of noise; for example, the median filter displays good performance in removing impulse noise, and the wavelet denoising algorithm displays good performance in removing Gaussian noise. However, images are affected by more than one type of noise in many cases. To reduce both impulse noise and Gaussian noise, this paper proposes a denoising method that combines adaptive median filtering (AMF) based on impulse noise detection with the wavelet threshold denoising method based on a Gaussian mixture model (GMM). The simulation results show that the proposed method achieves much better denoising performance than the median filter or the wavelet denoising method for images contaminated with mixed noise.

• 한국정보과학회논문지:소프트웨어및응용
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• 제35권7호
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• pp.417-423
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• 2008

본 논문에서는 각 음원이 시간적 구조를 가졌을 경우 음원들을 분리해내는 확률적 음원분리 방법을 제안한다. 이를 위해 각 음원의 시간적 구조를 가우시안 프로세스(Gaussian process)로 모델링하고 기존의 음원분리 문제를 유사-가능도 최대화 문제(pseudo-likelihood maximization)로 공식화한다. 본 알고리즘을 통해 얻어진 데이타의 유사-가능도는 정규 분포이며 이는 가우시안 프로세스 회귀방법(Gaussian process regression)을 통해 쉽게 계산이 가능하다. 음원분리의 역혼합 행렬은 경도(gradient) 기반최적화 기법을 통해 데이타의 유사-가능도를 최대화하는 해를 찾음으로써 구해진다. 여러 실험을 통하여 제안 알고리듬이 몇 가지 특정 상황에서 기존의 분리 알고리듬들에 비해 우수한 성능을 보임을 확인 할 수 있다.