• 상하수도학회지
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• 제22권6호
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• pp.609-617
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• 2008

Water pipes are supposed to deliver the predetermined demand safely to a certain point in water distribution system. However, pipe burst or crack can be happened due to so many reasons such as the water hammer, natural pipe ageing, external impact force, soil condition, and various environments of pipe installation. In the present study, the reliability model which can calculate the probability of pipe breakage was developed regarding unsteady effect such as water hammer. For the reliability model, reliability function was formulated by Barlow formula. AFDA method was applied to calculate the probability of pipe breakage. It was found that the statistical distribution for internal pressure among the random variables of reliability function has a good agreement with the Gumbel distribution after unsteady analysis was performed. Using the present model, the probability of pipe breakage was quantitatively calculated according to random variables such as the pipe diameter, thickness, allowable stress, and internal pressure. Furthermore, it was found that unsteady effect significantly increases the probability of pipe breakage. If this reliability model is used for the design of water distribution system, safe and economical design can be accomplished. And it also can be effectively used for the management and maintenance of water distribution system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.408-413
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• 2005

A new methodology for discrete non-Gaussian probability density estimation is investigated in this paper based on a dynamic Bayesian network (DBN) and kernel functions. The estimator consists of a DBN in which the transition distribution is represented with kernel functions. The estimator parameters are determined through a recursive learning algorithm according to the maximum likelihood (ML) scheme. A discrete-type Poisson distribution is generated in a simulation experiment to evaluate the proposed method. In addition, an unknown probability density generated by nonlinear transformation of a Poisson random variable is simulated. Computer simulations numerically demonstrate that the method successfully estimates the unknown probability distribution function (PDF).

• 한국생산제조학회지
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• 제18권4호
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• pp.395-400
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• 2009

As the variables affecting the fatigue behavior have uncertainty, the fatigue crack propagation is stochastic in nature. Therefore, the fatigue life prediction is critical for the design and the maintenance of many structural components. In this study, fatigue experiments are conducted on the specimens of magnesium alloy under the different thicknesses of specimen. The effects of specimen thickness on the probability distribution of the fatigue crack propagation life and the crack size are estimated experimentally. The probability distribution of the crack size and the fatigue life for different specimen thicknesses are investigated by Anderson-Darling test and the best fit for those probability distributions are also presented.

• 한국태양에너지학회 논문집
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• 제33권2호
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• pp.18-27
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• 2013

This paper presents a method for assessing the wind energy potential at complex terrain using probability distribution. And the proper probability models of the parameters estimating the wind energy are presented. Finally a mixture-Weibull determined by numerical methods procedure are proposed to assess the probability distribution of the energy potential at a site. The developed method is applied to the Kwanjungchun Bridge and compared with wind records which the neighboring weather station.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권2호
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• pp.116-120
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• 2008

Clustering is a method for unsupervised learning. General clustering tools have been depended on statistical methods and machine learning algorithms. One of the popular clustering algorithms based on machine learning is the self organizing map(SOM). SOM is a neural networks model for clustering. SOM and extended SOM have been used in diverse classification and clustering fields such as data mining. But, SOM has had a problem determining optimal number of clusters. In this paper, we propose an improvement of SOM using gap statistic and probability distribution. The gap statistic was introduced to estimate the number of clusters in a dataset. We use gap statistic for settling the problem of SOM. Also, in our research, weights of feature nodes are updated by probability distribution. After complete updating according to prior and posterior distributions, the weights of SOM have probability distributions for optima clustering. To verify improved performance of our work, we make experiments compared with other learning algorithms using simulation data sets.

• 한국환경과학회지
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• 제19권9호
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• pp.1153-1159
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• 2010

Identification of probability distribution for water quality constituents from specific land use is important to achieve successful implementation of TMDL program. In this 3-year study, distribution of discharge and BOD(Biological Oxygen Demand) concentration from paddy rice fields were monitored. Four probability distributions, normal, log-normal, Gamma and Weibull were fitted and the goodness-of-fit was assessed using probability plots and Kolmogorov-Smirnov test. $EMC_s$ of BOD in runoff from paddy field ranged 0.37 to $7.99\;mgL^{-1}$, and all four probability distributions were acceptable. But the normal distribution would be preferred for BOD from paddy fields considering nature of straight forward application.

• 품질경영학회지
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• 제27권4호
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• pp.143-152
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• 1999

In Shewhart control chart, the average run length(ARL) is calculated using the mean of a conventional geometric distribution(CGD) assuming a sequence of identical and independent Bernoulli trials. In this, the success probability of CGB is the probability that any point exceeds the control limits. When the process is in-control state, there is no problem in the above assumption since the probability that any point exceeds the control limits does not change if the in-control state continues. However, if the out-of-control state begins and continues during the process, the probability of exceeding the control limits may take two forms. First, once the out-of-control state begins with exceeding probability p, it continues with the same exceeding probability p. Second, after the out-of-control state begins, the exceeding probabilities may very according to some pattern. In the first case, ARL is the mean of CGD with success probability p as usual. But in the second case, the assumption of a sequence of identical and independent Bernoulli trials is invalid and we can not use the mean of CGD as ARL. This paper concentrate on that point. By adopting one generalized binomial distribution(GBD) model that allows correlated Bernoulli trials, generalized geometric distribution(GGD) is defined and its mean is derived to find an alternative ARL when the process is in out-of-control state and the exceeding probabilities take the second form mentioned in the above. Small-scale simulation is performed to show how an alternative ARL works.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.4184-4202
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• 2021

Text steganography combined with natural language generation has become increasingly popular. The existing methods usually embed secret information in the generated word by controlling the sampling in the process of text generation. A candidate pool will be constructed by greedy strategy, and only the words with high probability will be encoded, which damages the statistical law of the texts and seriously affects the security of steganography. In order to reduce the influence of the candidate pool on the statistical imperceptibility of steganography, we propose a steganography method based on a new sampling strategy. Instead of just consisting of words with high probability, we select words with relatively small difference from the actual sample of the language model to build a candidate pool, thus keeping consistency with the probability distribution of the language model. What's more, we encode the candidate words according to their probability similarity with the target word, which can further maintain the probability distribution. Experimental results show that the proposed method can outperform the state-of-the-art steganographic methods in terms of security performance.

• 한국인터넷방송통신학회논문지
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• 제17권6호
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• pp.59-68
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• 2017

무선 통신시스템에서 Random 과정을 해석적으로 표현할 수 있으며 적당한 확률분포를 구할 수 있다. 감쇄지수함수 확률분포에 의한 가우스, 레일레이, 나카가미 확률분포를 쉽게 유도했으며 시뮬레이션을 그림으로 보인다. 시간의 개념을 포함한 파형의 집합에 의한 확률적 표현이 Random과정(or Stochasic Process)인데 이를 무선환경의 조건에 따라 유도한다. 또한 가시거리 통신과 비가시거리 채널환경을 Rayleigh와 Rician 채널로 구체적인 예를 SISO, MIMO 환경에서 보인다. 또한, 본 논문에서 채널이 송신 블록 동안 일정하고 연속적인 송신 블록 사이에서 독립적으로 변하는 블록 페이딩 채널 모델을 가정함으로써 i.i.d 채널을 갖는 높은 SNR 영역에서 더 나은 성능을 얻을 수 있다는 동기를 부여한다. 이러한 변환을 실현하기 위한 알고리즘은 크로네 커 MIMO 채널에 적용 할 수 있다.

• 한국군사과학기술학회지
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• 제24권4호
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• pp.401-407
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• 2021

To confirm the change of muzzle velocity and the most suitable probability distribution model of the 155 mm K9 howitzer barrel with chrome plating and changed rifling. Using a statistical program, the muzzle velocity were plotted on a normal distribution, a 2-parameter and 3-parameter Weibull distribution on a probability paper. Also, statistical parameters were estimated and muzzle velocity fitness test and probability of K676 charge were plotted. In both the chrome-plated with standard rifling and changed rifling for K9 barrel, the 2-parameter and 3-parameter Weibull distribution were skewed to the left compared to the normal distribution. It was confirmed that the muzzle velocity of the K9 barrel with chromium-plated is suitable for the normal distribution and 3-parameter Weibull distribution model.