• 제목/요약/키워드: Probability distribution function

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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.

SOME PROPERTIES OF BIVARIATE GENERALIZED HYPERGEOMETRIC PROBABILITY DISTRIBUTIONS

  • Kumar, C. Satheesh
    • Journal of the Korean Statistical Society
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    • 제36권3호
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    • pp.349-355
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    • 2007
  • In this paper we study some important properties of the bivariate generalized hypergeometric probability (BGHP) distribution by establishing the existence of all the moments of the distribution and by deriving recurrence relations for raw moments. It is shown that certain mixtures of BGHP distributions are again BGHP distributions and a limiting case of the distribution is considered.

확률 분포 함수의 지수 곡선 접합을 이용한 RVE 적합성 평가 (Evaluation of RVE Suitability Based on Exponential Curve Fitting of a Probability Distribution Function)

  • 정상엽;윤태섭;한동석
    • 대한토목학회논문집
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    • 제30권5A호
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    • pp.425-431
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    • 2010
  • 2가지 이상의 재료로 구성된 다상(multi-phase) 재료는 상 분포에 따라 재료 특성이 다르기 때문에, 상 분포를 묘사할 수 있는 적절한 방법이 필요하다. 본 연구에서는 확률 분포 함수 two-point correlation function과 lineal-path function을 사용하여 재료 내부의 상 분포 상태를 확률적으로 묘사하였다. 수치 계산 방법으로 계산되는 확률 분포 함수를 3개의 매개 변수를 사용한 곡선 접합(curve fitting)을 이용하여 수식으로 표현하고, 적용성을 살펴보기 위하여 2상 합금 미세구조 가상 시편과 지반 모델 시편을 사용하였다. 이를 통해, 확률 분포 함수는 곡선 접합을 이용하여 지수 형태의 수식으로 표현이 가능하며, 이는 시편의 RVE로서의 활용 가능성을 판단하는데 사용될 수 있음을 확인하였다.

퍼지 클러스터링을 이용한 확률분포함수 기반의 다중문턱값 선정법 (Selection Method of Multiple Threshold Based on Probability Distribution function Using Fuzzy Clustering)

  • 김경범;정성종
    • 한국정밀공학회지
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    • 제16권5호통권98호
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    • pp.48-57
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    • 1999
  • Applications of thresholding technique are based on the assumption that object and background pixels in a digital image can be distinguished by their gray level values. For the segmentation of more complex images, it is necessary to resort to multiple threshold selection techniques. This paper describes a new method for multiple threshold selection of gray level images which are not clearly distinguishable from the background. The proposed method consists of three main stages. In the first stage, a probability distribution function for a gray level histogram of an image is derived. Cluster points are defined according to the probability distribution function. In the second stage, fuzzy partition matrix of the probability distribution function is generated through the fuzzy clustering process. Finally, elements of the fuzzy partition matrix are classified as clusters according to gray level values by using max-membership method. Boundary values of classified clusters are selected as multiple threshold. In order to verify the performance of the developed algorithm, automatic inspection process of ball grid array is presented.

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베타 확률분포를 이용한 입자 떼 최적화 알고리즘의 성능 비교 (On the Comparison of Particle Swarm Optimization Algorithm Performance using Beta Probability Distribution)

  • 이병석;이준화;허문범
    • 제어로봇시스템학회논문지
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    • 제20권8호
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    • pp.854-867
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    • 2014
  • This paper deals with the performance comparison of a PSO algorithm inspired in the process of simulating the behavior pattern of the organisms. The PSO algorithm finds the optimal solution (fitness value) of the objective function based on a stochastic process. Generally, the stochastic process, a random function, is used with the expression related to the velocity included in the PSO algorithm. In this case, the random function of the normal distribution (Gaussian) or uniform distribution are mainly used as the random function in a PSO algorithm. However, in this paper, because the probability distribution which is various with 2 shape parameters can be expressed, the performance comparison of a PSO algorithm using the beta probability distribution function, that is a random function which has a high degree of freedom, is introduced. For performance comparison, 3 functions (Rastrigin, Rosenbrock, Schwefel) were selected among the benchmark Set. And the convergence property was compared and analyzed using PSO-FIW to find the optimal solution.

Noncentral F-Distribution for an M-ary Phase Shift Keying Wedge-Shaped Region

  • Kim, Jung-Su;Chong, Jong-Wha
    • ETRI Journal
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    • 제31권3호
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    • pp.345-347
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    • 2009
  • This letter presents an alternative analytical expression for computing the probability of an M-ary phase shift keying (MPSK) wedge-shaped region in an additive white Gaussian noise channel. The expression is represented by the cumulative distribution function of known noncentral F-distribution. Computer simulation results demonstrate the validity of our analytical expression for the exact computation of the symbol error probability of an MPSK system with phase error.

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Context Probability를 Weighting Function으로 사용한 Contextual Classifier (Contextual Classifier with the Context Probability as a Weighting Function)

  • 노준경;박규호;김명환
    • 대한원격탐사학회지
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    • 제2권1호
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    • pp.3-11
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    • 1986
  • The current methods of estimating contest distribution function in contextual clarifier are to "classify and count", GTGM (ground-truth-guided-method) and unbiased estimator. In this paper we propose a new contextual classifier echoes context distribution is replaced by context probability that is estimated from transition probability. The classification accuracy increases considerably compared with the classical one.

와이블 분포함수를 이용한 하수관로 노후도 추정 (Estimation of sewer deterioration by Weibull distribution function)

  • 강병준;유순유;박규홍
    • 상하수도학회지
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    • 제34권4호
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    • pp.251-258
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    • 2020
  • Sewer deterioration models are needed to forecast the remaining life expectancy of sewer networks by assessing their conditions. In this study, the serious defect (or condition state 3) occurrence probability, at which sewer rehabilitation program should be implemented, was evaluated using four probability distribution functions such as normal, lognormal, exponential, and Weibull distribution. A sample of 252 km of CCTV-inspected sewer pipe data in city Z was collected in the first place. Then the effective data (284 sewer sections of 8.15 km) with reliable information were extracted and classified into 3 groups considering the sub-catchment area, sewer material, and sewer pipe size. Anderson-Darling test was conducted to select the most fitted probability distribution of sewer defect occurrence as Weibull distribution. The shape parameters (β) and scale parameters (η) of Weibull distribution were estimated from the data set of 3 classified groups, including standard errors, 95% confidence intervals, and log-likelihood values. The plot of probability density function and cumulative distribution function were obtained using the estimated parameter values, which could be used to indicate the quantitative level of risk on occurrence of CS3. It was estimated that sewer data group 1, group 2, and group 3 has CS3 occurrence probability exceeding 50% at 13th-year, 11th-year, and 16th-year after the installation, respectively. For every data groups, the time exceeding the CS3 occurrence probability of 90% was also predicted to be 27th- to 30th-year after the installation.

Robust Histogram Equalization Using Compensated Probability Distribution

  • Kim, Sung-Tak;Kim, Hoi-Rin
    • 대한음성학회지:말소리
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    • 제55권
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    • pp.131-142
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    • 2005
  • A mismatch between the training and the test conditions often causes a drastic decrease in the performance of the speech recognition systems. In this paper, non-linear transformation techniques based on histogram equalization in the acoustic feature space are studied for reducing the mismatched condition. The purpose of histogram equalization(HEQ) is to convert the probability distribution of test speech into the probability distribution of training speech. While conventional histogram equalization methods consider only the probability distribution of a test speech, for noise-corrupted test speech, its probability distribution is also distorted. The transformation function obtained by this distorted probability distribution maybe bring about miss-transformation of feature vectors, and this causes the performance of histogram equalization to decrease. Therefore, this paper proposes a new method of calculating noise-removed probability distribution by using assumption that the CDF of noisy speech feature vectors consists of component of speech feature vectors and component of noise feature vectors, and this compensated probability distribution is used in HEQ process. In the AURORA-2 framework, the proposed method reduced the error rate by over $44\%$ in clean training condition compared to the baseline system. For multi training condition, the proposed methods are also better than the baseline system.

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선원 행동오류에 대한 최적 확률분포함수 추정에 관한 연구 (A Study on the Estimation of Optimal Probability Distribution Function for Seafarers' Behavior Error)

  • 박득진;양형선;임정빈
    • 한국항해항만학회지
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    • 제43권1호
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    • pp.1-8
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    • 2019
  • 해양사고를 야기한 선원의 행동오류를 식별하는 것은 해양사고의 예방 또는 저감에 관한 연구의 기초가 된다. 본 연구의 목적은 선원들의 행동오류를 세 가지 행동(즉, Skill, Rule, Knowledge)으로 모델링하는데 필요한 최적의 확률분포함수를 추정하는데 있다. 본 저자들의 사전 연구에서 획득한 해양사고 종류별 행동오류 데이터를 이용하여 세 가지 행동오류에 최적인 확률분포함수를 추정하고, 확률분포함수에서 도출한 확률 값들 사이의 유의성을 검증하였다. 확률분포함수 추정에는 최우추정법(Maximum Likelihood Estimation, MLE)을 적용하고, 유의성 검증에는 분산분석(ANOVA)를 이용하였다. 실험결과 여덟 가지 해양사고 종류별 세 가지 행동으로 각각에 대해서 최소의 오차를 갖는 확률분포함수를 추정할 수 있었다. 이를 이용하여 계산한 여덟 가지의 해양사고 종류에 대한 세 가지 행동오류들의 확률 값들은 통계적인 유의성이 관측 되었다. 또한, 행동오류가 해양사고에 영향을 미치는 것으로 관측되었다.