• Water for future
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• v.7 no.2
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• pp.107-111
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• 1974

Annual runoff in the Nakdong river basin has been analyzed to find the probability functions of best fit to distribution of historical annual runoff. The results obtained are as follows; (1) Log-normal 3-parameter disrtibution is believed as the probability function of best fit to historical distribution (2) Log-normal 3-parameter disrtibution is believed as the best fit probability function among Log-normal dist-ributions. (3) In the test of goodness of fit, $x^2-test$ shows that probability of $x^2-valus$ in Log-normal 3-parameter distribution is nearly more than 90%. But in the Simirnov-Kolmogorov test, hypotheses for the probability distributions cannot be rejected at significance level 5% & 1%. (4) Among 7 gauging stations, Dongchon & Koryung-Bridge's records show lower fitness to the theoretical probability functions than other 5 gauging station's

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1826-1835
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• 2007

In this paper, we present a new approach for automatic detection and tracking for multiple targets. We combine a highest probability data association(HPDA) algorithm for target detection with a particle filter for multiple target tracking. The proposed approach evaluates the probabilities of one-to-one assignments of measurement-to-track and the measurement with the highest probability is selected to be target- originated, and the measurement is used for probabilistic weight update of particle filtering. The performance of the proposed algorithm for target tracking in clutter is compared with the existing clustering algorithm and the sequential monte carlo method for probability hypothesis density(SMC PHD) algorithm for multi-target detection and tracking. Computer simulation studies demonstrate that the HPDA algorithm is robust in performing automatic detection and tracking for multiple targets even though the environment is hostile in terms of high clutter density and low target detection probability.

• The Journal of Korea Robotics Society
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• v.4 no.1
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• pp.56-61
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• 2009

A probability-based data generation is a typical context-generation method that is a not only simple and strong data generation method but also easy to update generation conditions. However, the probability-based context-generation method has been found its natural-born ambiguousness and confliction problems in generated context data. In order to compensate for the disadvantages of the probabilistic random data generation method, a situation propagation network is proposed in this paper. The situation propagating network is designed to update parameters of probability functions are included in probability-based data generation model. The proposed probability-based context-generation model generates two kinds of contexts: one is related to independent contexts, and the other is related to conditional contexts. The results of the proposed model are compared with the results of the probabilitybased model with respect to performance, reduction of ambiguity, and confliction.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.292-297
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• 2003

A stochastic approach has been presented for superplastic deformation of Ti-6AJ-4V alloy, and probability function are used to heterogeneous phase distributions. The experimentally observed spatial correlation function are developed, and microstructural evolutions together with superplastic deformation behavior have investigated by means of the probability function. The result have shown that the probability varies approximately linearly with separation with distance, and significant deformation enhanced probability changes during the deformation. The stress-strain behavior with the evolutions of probability function can be correctly predicted by the model. The finite clement implementation using Monte Carlo simulation associated with phase re-distributions shows that better agreement with experimental data of failure strain on the test specimen.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.865-869
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• 2008

Juryeonggu is a Cuboctahedral die that had used in ancient Korea. This Cuboctahedral is consisted of different two penal servitudes of 14 facepieces, but the probability distribution can appear equally so it can be usable as a die. In this paper, achieved research study about probability of a Cuboctahedral die that have quadrilateral and triangle preferentially to search Juryeonggu's probability calculation method. First, confirmed probability distribution through Multibody-dynamics analysis and verified probability distribution through several experiments. Finally, with this simulation data, achieved theoretical analysis about Cuboctahedral die occurrence probability by using the residual momentum energy.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.183-190
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• 2017

PURPOSES : The objective of this study is to establish the traffic volume-based warrants of right-turn lanes at unsignalized intersections and to introduce a risk probability methodology based on the warrants. METHODS : In this study, a risk probability of a potential rear-end collision is applied between a right-turn vehicle and the immediately following through vehicle. Using the shifted negative exponential model and the compound probability theorem, the risk probability can be expressed as the function of directional volumes and the percentage of right-turns for a two-lane and four-lane highway, respectively. RESULTS : Based on the risk probablity, guidelines for installing right-turn lanes on two-lane and four-lane highways were developed. The risk probability also showed rationality by comparing with right-turn same-direction conflicts observed in-situ. CONCLUSIONS : The results of our study define the total approaching volumes to encourage a right-turn lane as a function of operating speed, percentage of right-turn, and number of lanes.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.5
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• pp.536-543
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• 2009

In this paper the mean stress effects on the probability distribution of the random grown crack size at a specified loading cycle are studied through the fatigue crack propagation tests, which are conducted on the specimens of magnesium alloy under four different stress ratios. Through 80 replicates the probability distributions of the grown crack size are obtained. The goodness-of-fit for probability distributions of the random grown crack size are investigated by Anderson-Darling test and the best fit for those probability distributions is found to be a 3-parameter Weibull distribution. The effects of the mean stress on the probability distribution of the random grown crack size are also estimated.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.3
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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.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.2
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• pp.16-22
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• 1983

In this paper, we obtained PFME(probability for maximum entropy) and entropy when a conditional probability was given in a binary list order Markov Information Source. And, when steady state probability was constant, the influence of change of a conditional probability on entropy was examined, too.