• 제목/요약/키워드: Gaussian distribution

검색결과 919건 처리시간 0.035초

Non-Gaussian time-dependent statistics of wind pressure processes on a roof structure

  • Huang, M.F.;Huang, Song;Feng, He;Lou, Wenjuan
    • 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.

임의의 표본상호상관함수와 비정규확률분포를 갖는 다중 난류시계열의 디지털 합성방법을 이용한 풍속데이터 시뮬레이션 (Wind Data Simulation Using Digital Generation of Non-Gaussian Turbulence Multiple Time Series with Specified Sample Cross Correlations)

  • 성승학;김욱;김경천;부정숙
    • 한국대기환경학회지
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    • 제19권5호
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    • pp.569-581
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    • 2003
  • A method of synthetic time series generation was developed and applied to the simulation of homogeneous turbulence in a periodic 3 - D box and the hourly wind data simulation. The method can simulate almost exact sample auto and cross correlations of multiple time series and control non-Gaussian distribution. Using the turbulence simulation, influence of correlations, non-Gaussian distribution, and one-direction anisotropy on homogeneous structure were studied by investigating the spatial distribution of turbulence kinetic energy and enstrophy. An hourly wind data of Typhoon Robin was used to illustrate a capability of the method to simulate sample cross correlations of multiple time series. The simulated typhoon data shows a similar shape of fluctuations and almost exactly the same sample auto and cross correlations of the Robin.

LATITUDINAL DISTRIBUTION OF SUNSPOTS AND DURATION OF SOLAR CYCLES

  • CHANG, HEON-YOUNG
    • 천문학회지
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    • 제48권6호
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    • pp.325-331
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    • 2015
  • We study an association between the duration of solar activity and characteristics of the latitude distribution of sunspots by means of center-of-latitude (COL) of sunspots observed during the period from 1878 to 2008 spanning solar cycles 12 to 23. We first calculate COL by taking the area-weighted mean latitude of sunspots for each calendar month to determine the latitudinal distribution of COL of sunspots appearing in the long and short cycles separately. The data set for the long solar cycles consists of the solar cycles 12, 13, 14, 20, and 23. The short solar cycles include the solar cycles 15, 16, 17, 18, 19, 21, and 22. We then fit a double Gaussian function to compare properties of the latitudinal distribution resulting from the two data sets. Our main findings are as follows: (1) The main component of the double Gaussian function does not show any significant change in the central position and in the full-width-at-half-maximum (FWHM), except in the amplitude. They are all centered at ~ 11° with FWHM of ~ 5°. (2) The secondary component of the double Gaussian function at higher latitudes seems to differ in that even though their width remains fixed at ~ 4°, their central position peaks at ~ 22.1° for the short cycles and at ~ 20.7° for the long cycles with quite small errors. (3) No significant correlation could be established between the duration of an individual cycle and the parameters of the double Gaussian. Finally, we conclude by briefly discussing the implications of these findings on the issue of the cycle 4 concerning a lost cycle.

우리나라 연안의 기온과 수온 분포함수 추정 및 비교평가 (Estimation and Comparative Analysis on the Distribution Functions of Air and Water Temperatures in Korean Coastal Seas)

  • 조홍연;정신택
    • 한국해안·해양공학회논문집
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    • 제28권3호
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    • pp.171-176
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    • 2016
  • 기온과 수온의 분포형태는 발생빈도의 양상을 결정하는 기본적이고 필수적인 정보이다. 또한 기후변화에 의한 기온과 수온의 장기변화 양상 파악에 유용하다. 기온과 수온의 전형적인 분포형태는 다수의 첨두(mode)를 가지는 형태로 일반적으로 널리 사용되는 정규분포로 표현하기에는 한계가 있다. 본 연구에서는 Gaussian 혼합함수와 Kernel 분포함수를 보다 기온과 수온의 보다 적합한 분포함수 형태로 제안한다. 제안된 분포함수를 우리나라 연안 기온과 수온자료를 이용하여 추정-평가한 결과, 관측 자료의 분포는 꼬리 영역에서 크게 차이를 보이고 있는 것으로 파악되었다. 높은 수온영역과 낮은 기온 영역에서 꼬리 영역이 길게 나타나고 있다. 또한 본 연구에서 제안한 분포함수 추정 및 비교는 기온과 수온의 상호 변동관계 및 장기적인 변동양상을 파악할 수 있다. 그러나 평균 기온 및 수온 그리고 정규분포 함수 형태로는 이러한 변화 양상의 파악은 크게 제한되고 있다.

Estimating Suitable Probability Distribution Function for Multimodal Traffic Distribution Function

  • Yoo, Sang-Lok;Jeong, Jae-Yong;Yim, Jeong-Bin
    • 해양환경안전학회지
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    • 제21권3호
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    • pp.253-258
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    • 2015
  • The purpose of this study is to find suitable probability distribution function of complex distribution data like multimodal. Normal distribution is broadly used to assume probability distribution function. However, complex distribution data like multimodal are very hard to be estimated by using normal distribution function only, and there might be errors when other distribution functions including normal distribution function are used. In this study, we experimented to find fit probability distribution function in multimodal area, by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. By using chi-squared statistic, gaussian mixture model(GMM) is the fittest model rather than other distribution functions, such as extreme value, generalized extreme value, logistic, and normal distribution. GMM was found to the fit model regard to multimodal data of maritime traffic flow distribution. Probability density function for collision probability and traffic flow distribution will be calculated much precisely in the future.

Meta-Gaussian 방법을 이용한 강우-유출 모형에서의 불확실성 산정 (Evaluation of the Uncertainties in Rainfall-Runoff Model Using Meta-Gaussian Approach)

  • 김병식;김보경;권현한
    • 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.

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기-고 유동층에서 Gaussian 분포 입자군의 표준편차에 따른 유출 특성 (The Characteristics of Elutriation with Gaussian Particle Size Distributions in a gas-solid fluidized bed)

  • 장현태;차왕석
    • 한국산학기술학회논문지
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    • 제10권11호
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    • pp.3274-3279
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    • 2009
  • 기-고 유동층에서 다입자경 입자의 입자분포 변화에 따른 비산유출 특성을 연구하였다. 다입자경 입자분포는 Gaussian 분포를 사용하여 실험을 수행하였다. 최소유동화속도에 대한 유속비와 Gaussian 입자분포의 표준편차에 따른 비산유출상수를 구하였으며, 이때 조업시간에 따른 압력요동의 특성치를 구하였다. 측정된 유동층의 압력요동 특성치로부터 압력요동의 표준편차, 평균압력, Power spectrum density function, 주진동수 등을 계산하였다. 입자분포군에 따라서 유출입자의 입자분포 및 압력요동 특성치는 크게 영향을 받는 것으로 나타났으며 이러한 결과로부터 압력요동 특성치로부터 유출특성의 해석이 가능함을 알 수 있었다.

Non-parametric Density Estimation with Application to Face Tracking on Mobile Robot

  • Feng, Xiongfeng;Kubik, K.Bogunia
    • 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 ...

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Asymptotic Gaussian Structures in a Critical Generalized Curie-Wiss Mean Field Model : Large Deviation Approach

  • Kim, Chi-Yong;Jeon, Jong-Woo
    • Journal of the Korean Statistical Society
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    • 제25권4호
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    • pp.515-527
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    • 1996
  • It has been known for mean field models that the limiting distribution reflecting the asymptotic behavior of the system is non-Gaussian at the critical state. Recently, however, Papangelow showed for the critical Curie-Weiss mean field model that there exist Gaussian structures in the asymptotic behavior of the total magnetization. We construct Gaussian structures existing in the internal fluctuation of the system for the critical case of a generalized Curie-Weiss mean field model.

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Likelihood Based Inference for the Shape Parameter of the Inverse Gaussian Distribution

  • Lee, Woo-Dong;Kang, Sang-Gil;Kim, Dong-Seok
    • Communications for Statistical Applications and Methods
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    • 제15권5호
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    • pp.655-666
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    • 2008
  • Small sample likelihood based inference for the shape parameter of the inverse Gaussian distribution is the purpose of this paper. When shape parameter is of interest, the signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic are derived. Hsieh (1990) gave a statistical inference for the shape parameter based on an exact method. Throughout simulation, we will compare the statistical properties of the proposed statistics to the statistic given by Hsieh (1990) in term of confidence interval and power of test. We also discuss a real data example.