• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.6
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• pp.544-550
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• 2009

To analyze the threat decision performance of MWR(Missile Warning Radar) give analysis on condition that we decide the effective threat using the POC(Probability of Over Countermeasure)/PUC(Probability of Under Countermeasure). Thus, we execute the simulation using the Monte-Carlo method to analyze effect, but the execution time of simulation took longer than we expected. In this paper, the effect analysis is proposed using the probability model to reduce the execution time of simulation. We present the setting method of parameter for probability model and the effect analysis result of MWR using the simulation. Also, we present the comparison result of simulation execution time for Monte-Carlo and probability model.

• Journal of Environmental Science International
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• v.20 no.3
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• pp.329-340
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• 2011

The probability concepts mainly used for rainfall or flood frequency analysis in water resources planning are the frequentist viewpoint that defines the probability as the limit of relative frequency, and the unknown parameters in probability model are considered as fixed constant numbers. Thus the probability is objective and the parameters have fixed values so that it is very difficult to specify probabilistically the uncertianty of these parameters. This study constructs the uncertainty evaluation model using Bayesian MCMC and Metropolis -Hastings algorithm for the uncertainty quantification of parameters of probability distribution in rainfall frequency analysis, and then from the application of Bayesian MCMC and Metropolis- Hastings algorithm, the statistical properties and uncertainty intervals of parameters of probability distribution can be quantified in the estimation of probability rainfall so that the basis for the framework configuration can be provided that can specify the uncertainty and risk in flood risk assessment and decision-making process.

• Journal of Educational Research in Mathematics
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• v.19 no.2
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• pp.233-256
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• 2009

The notions of conditional probability and independence are fundamental to all aspects of probabilistic reasoning. Several previous studies identified some misconceptions in students' thinking in conditional probability. However, they have not analyzed enough the nature of conditional probability. The purpose of this study was to analyze conditional probability and students' knowledge on conditional probability. First, we analyzed the conditional probability from mathematical, historico-genetic, psychological, epistemological points of view, and identified the essential aspects of the conditional probability. Second, we investigated the high school students' and undergraduate students' thinking m conditional probability and independence. The results showed that the students have some misconceptions and difficulties to solve some tasks with regard to conditional probability. Based on these analysis, the characteristics of reasoning about conditional probability are investigated and some suggestions are elicited.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.3
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• pp.63-70
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• 2018

In this study, a simple probabilistic approach using equivalent coefficient of consolidation ($c_e$) was proposed to consider the spatial variability of coefficient of vertical consolidation ($c_v$), and the effect of the probability distribution of coefficient of consolidation on degree of consolidation in heterogeneous soil was investigated. The statistical characteristics of consolidation coefficient were estimated from 1,226 field data, and four probability distributions (Normal, Log-normal, Gamma, and Weibull) were applied to consider the effect of probability distribution. The random fields of coefficient of consolidation were generated based on Karhunen-Loeve expansion. Then, the equivalent coefficient of consolidation was calculated from the random field and used as the input value of consolidation analysis. As a result, the probabilistic analysis can be performed effectively by separating random field and numerical analysis, and probabilistic analysis was performed using a Latin hypercube Monte Carlo simulation. The results showed that the statistical properties of $c_e$ were changed by the probability distribution and spatial variability of $c_v$, and the probability distribution of $c_v$ has considerable effects on the probabilistic results. There was a large difference of failure probability depend on the probability distribution when the autocorrelation distance was small (i.e., highly heterogeneous soil). Therefore, the selection of a suitable probability distribution of $c_v$ is very important for reliable probabilistic analysis of consolidation.

• Korean Journal of Mathematics
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• v.28 no.2
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• pp.323-341
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• 2020

In this note, we investigate the multifractal analogues of the Hewitt-Stromberg measures and dimensions in a probability space.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.3
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• pp.332-338
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• 2018

To perform the Maritime Safety Audi Scheme, $10^{-4}$ was constantly applied without adjustment when evaluating the proximity of the fairway. The necessity of applying the different aberrancy probabilities from the different proximity of the fairway depending on the shape of the route and the size of the ship was validated using marine simulations. Marine simulation was performed to evaluate the validity of statistical analysis-based aberrancy probability according to the different shapes of routes and ship size presented in the previous study. As results, the validity of the criterion of the statistical analysis-based aberrancy probability was confirmed by comparing with the results of simulation-based aberrancy probabilities. The results support that the aberrancy probabilities by the types of a vessel could be different based on the type and size of vessels. The results motivate that further investigation is required to find the reasonable criteria of the aberrancy probabilities for the maritime traffic safety audit according to the fairway shape and the size of the vessel.

• Structural Engineering and Mechanics
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• v.57 no.4
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• pp.587-602
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• 2016

In structural reliability analysis, the response surface method is widely adopted because of its numerical efficiency. It should be understood that the response function must approximate the actual limit state function accurately in the main region influencing failure probability where it is evaluated. However, the size of main region influencing failure probability was not defined clearly in current response surface methods. In this study, the concept of sub-region of interest is constructed, and an improved response surface method is proposed based on the sub-region of interest. The sub-region of interest can clearly define the size of main region influencing failure probability, so that the accuracy of the evaluation of failure probability is increased. Some examples are introduced to demonstrate the efficiency and the accuracy of the proposed method for both numerical and implicit limit state functions.

• Research in Mathematical Education
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• v.15 no.2
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• pp.127-140
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• 2011

"Statistical literacy" is important to be an effective citizen ([Gal, I. (2005). Towards "probability literacy" for all citizens: Building blocks and instructional dilemmas. In: G. A. Jones (Ed.), Exploring probability in school: Challenges for teaching and learning (pp. 39-63). New York: Springer]). Probability and statistics has been connected with real context and can be used to stimulate students' creative abilities. This study aims at identifying the extent that textbooks in three countries include experimental probability concepts and non-routine, open-ended, application and contextual problems. How well textbooks reflect real application situations is important in the sense that students can employ probability concepts when solving real world problems. Results showed that three textbook series did not mention experimental probability. Furthermore, all of text-books had more routine, close-ended, knowing, and non-contextual problems.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.8
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• pp.31-37
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• 2019

The inter-development of FMECA is very important to assess the effect of potential failures during system operation on mission, safety and performance. Among these, criticality analysis is a core task that identifies items with high risk and selects the analyzed objects as the key management targets and reflects their effects to the design optimization. In this paper, we analyze the theory related to criticality analysis following US military standard, and propose a method to quantify the failure effect probability for objective criticality analysis. The criticality analysis according to the US military standard depends on the subjective judgment of the failure probability. The methodology for quantifying the failure effect probability is presented by using the reliability theory and the Bayes theorem. The failure rate is calculated by applying the method to quantify failure effect probability.