• Journal of Korean Society for Quality Management
• /
• v.23 no.3
• /
• pp.113-125
• /
• 1995

This paper describes the 2-stage randomized response model in the Bayesian view point. The classical Bayesian analysis needs the complete information for a prior density, but the Bayes linear estimator needs only the first and second moments. Therefore, it is convenient to find the estimator and this estimator robusts to a prior density. We show that MSE's of the Bayes linear estimators for the 2-stage randomized response models are smaller than those of the MLE's for the 2-stage randomized response models.

• Journal of Korea Water Resources Association
• /
• v.42 no.6
• /
• pp.465-480
• /
• 2009

In this study, single and multiple linear regression model were used to derive the relationship between precipitation and altitude, latitude and longitude in Jejudo. The single linear regression analysis was focused on whether orographic effect was existed in Jejudo by annual average precipitation, and the multiple linear regression analysis on whether orographic effect was applied to each duration and return period of quantile from regional frequency analysis by index flood method. As results of the regression analysis, it shows the relationship between altitude and precipitation strongly form a linear relationship as the length of duration and return period increase. The multiple linear regression precipitation estimates(which used altitude, latitude, and longitude information) were found to be more reasonable than estimates obtained using altitude only or altitude-latitude and altitude-longitude. Especially, as results of spatial distribution analysis by kriging method using GIS, it also provides realistic estimates for precipitation that the precipitation was occurred the southeast region as real climate of Jejudo. However, the accuracy of regression model was decrease which derived a short duration of precipitation or estimated high region precipitation even had long duration. Consequently the other factor caused orographic effect would be needed to estimate precipitation to improve accuracy.

• Journal of the Korean Society for Railway
• /
• v.18 no.4
• /
• pp.374-390
• /
• 2015

This research shows the relationship between the number of trains and the probability of trains with arrival delay and suggests way to estimate the benefits of improved punctuality in a bottleneck section of the Gyeongbu Line. The arrival delays of high-speed and conventional trains were estimated using the train operation data of KORAIL. Linear regression models for the probability of trains with arrival delay by train type are presented in this paper. The probabilities of trains with arrival delay were more affected by the number of conventional trains than by the number of high-speed rail trains. For the empirical analysis, a project for increasing the capacity in the Seoul~Geumcheongu office section was tested. The benefits of the improved punctuality were estimated to be 4.2~4.5 billion Korean won every year. This research has some limitations but it can help evaluate more precisely the feasibility of the project of increasing the capacity in bottleneck sections.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.2D
• /
• pp.251-258
• /
• 2006

This study is to develop an estimation method of freeway design capacity through the analysis of time headway distribution in continuum flow. Traffic flow-speed diagram and time headway distribution plotted from individual vehicle data shows: a) a road capacity is not deterministic but stochastic, b) time headway distribution for each vehicle speed group follows pearson type V distribution. The freeway design capacity estimation model is developed by determining a minimum time headway for capacity with stochastic method. The estimated capacity values for each design speed are lower when design speed ${\leq}80km/h$, and higher when design speed ${\geq}106km/h$ in comparison with HCM(2000)'s values. In addition, The distinguish difference is that this model leads flexible application in planning level by defining the capacity as stochastic distribution. In detail, this model could prevent a disutility to add a lane for only one excess demand in a road planning level.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.391-404
• /
• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Journal of Korea Water Resources Association
• /
• v.55 no.10
• /
• pp.723-736
• /
• 2022

In this study, monthly precipitation forecasting models that can predict up to 12 months in advance were constructed for the Geum River basin, and two statistical techniques, multiple linear regression (MLR) and artificial neural network (ANN), were applied to the model construction. As predictor candidates, a total of 47 climate indices were used, including 39 global climate patterns provided by the National Oceanic and Atmospheric Administration (NOAA) and 8 meteorological factors for the basin. Forecast models were constructed by using climate indices with high correlation by analyzing the teleconnection between the monthly precipitation and each climate index for the past 40 years based on the forecast month. In the goodness-of-fit test results for the average value of forecasts of each month for 1991 to 2021, the MLR models showed -3.3 to -0.1% for the percent bias (PBIAS), 0.45 to 0.50 for the Nash-Sutcliffe efficiency (NSE), and 0.69 to 0.70 for the Pearson correlation coefficient (r), whereas, the ANN models showed PBIAS -5.0~+0.5%, NSE 0.35~0.47, and r 0.64~0.70. The mean values predicted by the MLR models were found to be closer to the observation than the ANN models. The probability of including observations within the forecast range for each month was 57.5 to 83.6% (average 72.9%) for the MLR models, and 71.5 to 88.7% (average 81.1%) for the ANN models, indicating that the ANN models showed better results. The tercile probability by month was 25.9 to 41.9% (average 34.6%) for the MLR models, and 30.3 to 39.1% (average 34.7%) for the ANN models. Both models showed long-term predictability of monthly precipitation with an average of 33.3% or more in tercile probability. In conclusion, the difference in predictability between the two models was found to be relatively small. However, when judging from the hit rate for the prediction range or the tercile probability, the monthly deviation for predictability was found to be relatively small for the ANN models.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.28 no.2
• /
• pp.63-72
• /
• 2016

An expected-discounted cost model based on RRP(Renewal Reward Process), referred to as a stochastic decision model, has been developed to estimate the optimal period of in-depth inspection which is one of critical issues in the life-cycle maintenance management of harbor structures such as rubble-mound breakwaters. A mathematical model, which is a function of the probability distribution of the service-life, has been formulated by simultaneously adopting PIM(Periodic Inspection and Maintenance) and CBIM(Condition-Based Inspection and Maintenance) policies so as to resolve limitations of other models, also all the costs in the model associated with monitoring and repair have been discounted with time. From both an analytical solution derived in this paper under the condition in which a failure rate function is a constant and the sensitivity analyses for the variety of different distribution functions and conditions, it has been confirmed that the present solution is more versatile than the existing solution suggested in a very simplified setting. Additionally, even in that case which the probability distribution of the service-life is estimated through the stochastic process, the present model is of course also well suited to interpret the nonlinearity of deterioration process. In particular, a MCS(Monte-Carlo Simulation)-based sample path method has been used to evaluate the parameters of a damage intensity function in stochastic process. Finally, the present stochastic decision model can satisfactorily be applied to armor units of rubble mound breakwaters. The optimal periods of in-depth inspection of rubble-mound breakwaters can be determined by minimizing the expected total cost rate with respect to the behavioral feature of damage process, the level of serviceability limit, and the consequence of that structure.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.5B
• /
• pp.471-477
• /
• 2010

In this study, the variability of the Horton index which is ratio of vaporization and wetting water is investigated using a conceptual soil water balance model. From the proposed model, the steady-state soil water probabilistic density function is derived through meteorological and watershed characteristics and then the sensitivity of Horton index to the precipitation occurrence rate and the mean of wet day precipitation is examined. As a result, the inter-annual variability of the Horton index is lower than that of precipitation and they showed the strong negative correlation. It is also shown that although precipitation is not varied, the Horton index can be varied due to the fluctuation of the precipitation occurrence rate and the mean of wet day precipitation. In addition, it is presented that there is a non-linear relationship which has a critical point switching proportional or inverse relationship between the Horton index and two main characteristics of precipitation process.

• Journal of Korea Water Resources Association
• /
• v.38 no.1
• /
• pp.1-9
• /
• 2005

The study shows the possible use of the index flood frequency curves for an estimation of flood quantiles at ungauged locations. Flood frequency analysis were made for the annual maximum flood data series at 9 available stations in the Han river basin. From the flood frquency curve at each station the mean annual flood of 2.33-year return period was determined and the ratios of the flood magnitude of various return period to the mean annual flood at each station were averaged throughout the Han river basin, resulting mean flood ratios of different return periods. A correlation analysis was made between the mean annual flood and physiographic parameters of the watersheds i.e, the watershed area and mean river channel slope, resulting an empirical multiple linear regression equation over the whole Han river basin. For unguaged watershed the flood of a specified return period could be estimated by multiplying the mead flood ratio corresponding the return period with the mean annual flood computed by the empirical formula developed in terms of the watershed area and river channel slope. To verify the applicability of the methodology developed in the present study the floods of various return periods determined for the watershed in the river channel improvement plan formulation by the Ministry of Construction and Transportation(MOCT) were compared with those estimated by the present method. The result proved a resonable agreement up to the watershed area of approximately 2,000k $m^2$. It is suggested that the practice of design flood estimation based on the rainfall-runoff analysis might have to be reevaluated because it involves too much uncertainties in the hydrologic data and rainfall-runoff model calibration.

• Korean journal of applied entomology
• /
• v.50 no.3
• /
• pp.235-245
• /
• 2011

Temperature-related parameters of Panonychus citri (McGregor) (Acarina: Tetranychidae) development were estimated and a stage-structured matrix model was developed. The lower threshold temperatures were estimated as $8.4^{\circ}C$ for eggs, $9.9^{\circ}C$ for larvae, $9.2^{\circ}C$ for protonymphs, and $10.9^{\circ}C$ for deutonymphs. Thermal constants were 113.6, 29.1, 29.8, and 33.4 degree days for eggs, larvae, protonymphs, and deutonymphs, respectively. Non-linear development models were established for each stage of P. citri. In addition, temperature-dependent total fecundity, age-specific oviposition rate, and age-specific survival rate models were developed for the construction of an oviposition model. P. citri age was categorized into five stages to construct a matrix model: eggs, larvae, protonymphs, deutonymphs and adults. For the elements in the projection matrix, transition probabilities from an age class to the next age class or the probabilities of remaining in an age class were obtained from development rate function of each stage (age classes). Also, the fecundity coefficients of adult population were expressed as the products of adult longevity completion rate (1/longevity) by temperature-dependent total fecundity. To evaluate the predictability of the matrix model, model outputs were compared with actual field data in a cool early season and hot mid to late season in 2004. The model outputs closely matched the actual field patterns within 30 d after the model was run in both the early and mid to late seasons. Therefore, the developed matrix model can be used to estimate the population density of P. citri for a period of 30 d in citrus orchards.