• Structural Monitoring and Maintenance
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• v.2 no.1
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• pp.49-64
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• 2015

This paper presents a method for assessing the risk of wave run-up and overtopping of existing coastal defences and for analysing the probability of failure of the structures under future hydraulic conditions. The recent UK climate projections are employed in the investigations of the influence of changing environments on the long-term performance of sea defences. In order to reduce the risk of wave run-up and overtopping caused by rising sea level and to maintain the present-day allowances for wave run-up height and overtopping discharge, the future necessary increase in crest level of existing structures is investigated. Various critical failure mechanisms are considered for reliability analysis, i.e., erosion of crest by wave overtopping, failure of seaside revetment, and internal erosions within earth sea dykes. The time-dependent reliability of sea dykes is analysed to give probability of failure with time. The results for an example earth dyke section show that the necessary increase in crest level is approximately double of sea level rise to maintain the current allowances. The probability of failure for various failure modes of the earth dyke has a significant increase with time under future hydraulic conditions.

• Journal of Environmental Science International
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• v.28 no.1
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• pp.19-35
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• 2019

This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.59-66
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• 2011

This work presents an algorithm for generating multi-RUN (m-RUN) deadlock avoidance policy based on simulated annealing algorithm. The basic idea of this method is to gradually improve the current m-RUN DAP after constructing an initial m-DAP by using simple m RUN DAPs. The search for a neighbor of the current m-RUN DAP is done by selecting and changing only one component of the current m-RUN, while accepting some unimproved solutions with some probability. It is examined for its performance by generating some sample system configurations.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.281-287
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• 2020

In capital budgeting practices, investment project evaluations based on the net present value (NPV) and the internal rate of return (IRR) represent the traditional evaluation techniques. Compared with the traditional methods, the modified internal rate of return (MIRR) gives the opportunity to evaluate an investment in certain projet, while taking the changes in cash flows over time and issuing shares such as dividing shares, bonuses, and dividend for each end of the investment year into account. Therefore, this study aims to evaluate an investment in the Malaysian construction sector utilizing financial data for 39 public listed companies operating in the Malaysian construction sector over the period from Jan 1, 2007, to December 30, 2018, based on the MIRR method. Stochastic was studied in this study to estimate the estimated probability by applying the Markov chain model to the MIRR method where the transition matrix has two possible movements of either Good (G) or Bad (B). it is found that the long-run probability of getting a good investment is higher than the probability of getting a bad investment in the long-run, where were the probabilities of good and bad are 0.5119, 0.4881, respectively. Hence, investment in the Malaysian construction sector is recommended.

• Korean Journal of Organic Agriculture
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• v.29 no.3
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• pp.359-384
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• 2021

In a long-run, a price reduction of shine muscat that is one type of grapes is expected due to an increase of cultivated area. To come up with this problem, expanding exports of shine muscat considering that domestic demand is restricted in Korea. This study investigates the China consumers preference for shine muscat from Korea since exports to China have increased a lot after the quarantine agreement in 2015. Specifically, this paper analyzes a probability of shine muscat exports to China based on willingness to pay (WTP). Moreover, we derive long-run and short-run export strategies for Korean shine muscat. Our results show that a probability of exports to China is high. However, this probability is lowered at the sample of consumers who have the experience of tasted shine muscat. Considering the relative important characteristic for buying shine muscat at the sample of eating experienced consumers in China is sweetness, there is a need to develop cultivation technologies for enhancing sweetness to attain a sustainable development in the grape sector of Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.479-483
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• 2004

A new calculation method of expected overtopping probability of rubble mound breakwater considering real tide occurrence has been proposed. A calculation method of expected overtopping probability of rubble mound breakwater was proposed by Kweon and Suh (2003). In their calculation, the fluctuation of tidal elevation was expressed by the sinusoidal change that yields the uniform distribution of occurrence frequency. However, the realistic distribution of tidal elevation should influence on the overtopping chance. In this study, the occurrence frequency of tidal elevation obtained from the real sea is included. The tidal elevation used in this study is collected from the east coastal part of Korean peninsular. Analyzing the annual data of the tidal fluctuation measured hourly during 355 days, the distribution of occurrence frequency is formulated utilizing by the normal distribution with one peak. Among the calculation procedures of annual maximum wave height, wave height-period joint distribution, wave run-up height and occurrence frequency of tide, only the annual maximum wave height is again chosen randomly from normal distribution to consider the uncertainty. The others are treated by utilizing the distribution function or relationship itself, It is found that the inclusion of the variability of tidal elevation has great influence on the computation of the expected overtopping probability of rubble mound breakwater. The bigger standard deviation of occurrence frequency is, the lower the overtopping probability of rubble mound breakwater is.

• Kyungpook Mathematical Journal
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• v.64 no.2
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• pp.287-301
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• 2024

From the mathematical and statistical point of view, a segment of a DNA strand can be viewed as a sequence of four-state (A, C, G, T) trials. Herein, we consider the distributions of runs and patterns related to the run lengths of multi-state sequences, especially for four states (A, B, C, D). Let X₁, X₂, . . . be a sequence of four state independent and identically distributed trials taking values in the set 𝒢 = {A, B, C, D}. In this study, we obtain exact formulas for the probability distribution function for the discrete distribution of runs of B's of order k. We obtain longest run statistics, shortest run statistics, and determine the distributions of waiting times and run lengths.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.5
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• pp.116-122
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• 2014

In this study, 2 kinds of twist run models as exercise equipments are compared by durability analyses of fatigue and vibration. Maximum equivalent stresses are shown as 3.3 MPa and 16.6 MPa at the parts of stress concentrations at models 1 and 2. As the values becomes much lower than yield stress of this models, these models are shown to be safe designs. Model 1 becomes stronger than model 2 at natural frequency analysis. Fatigue lives become lowest at four axis parts and one axis part respectively in cases of models 1 and 2. Maximum damage probability at fatigue is shown to be 2.4% near the average stress of 0 in case of model 1 but this probability becomes 0.6 % in case of model 2. Model 1 has the maximum damage possibility 4 times more than model 2 at these states. As the result of this study is applied by the design of twist run, the prevention on fatigue damage and the durability are predicted.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.499-511
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• 2000

We consider a stable tandem network which consists of two M/M/1 nodes and study the probability that the total backlog exceeds a large level N. Since the excessive backlog is a rare event, it is difficult to estimate this probability efficiently by using the crude Monte Carlo simulation. Instead we perform the ;$h$-transform proposed by McDonald(1999) to obtain the twisted network, in which the node with the larger load is overloaded. Then we use it to run the fast simulation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.