• Journal of Korean Society of Steel Construction
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• v.20 no.1
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• pp.21-31
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• 2008

response surface method (RSM) is widely used to evaluate th e extremely smal probability of ocurence or toanalyze the reliability of very complicated structures. Althoug h Monte-Carlo Simulation (MCS) technique can evaluate any system, the procesing time of MCS dependson the reciprocal num ber of the probability of failure. The stochastic finite element method could solve thislimitation. However, it is limit ed to the specific program, in which the mean and coeficient o f random variables are programed by a perturbation or by a weigh ted integral method. Therefore, it is not aplicable when erequisite programing. In a few number of stage analyses, RSM can construct a regresion model from the response of the c omplicated structural system, thus, saving time and efort significantly. However, the acuracy of RSM depends on the dist ance of the axial points and on the linearity of the limit stat e functions. To improve the convergence in exact solution regardl es of the linearity limit of state functions, an improved adaptive response surface method is developed. The analyzed res ults have ben verified using linear and quadratic forms of response surface functions in two examples. As a result, the be st combination of the improved RSM techniques is determined and programed in a numerical code. The developed linear adapti ve weighted response surface method (LAW-RSM) shows the closest converged reliability indices, compared with quadratic form or non-adaptive or non-weighted RSMs.

• Journal of Korea Water Resources Association
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• v.45 no.12
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• pp.1321-1330
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• 2012

In this study, the daily inflow at the basin of Chungju dam is predicted using wavelet-artificial neural network for nonlinear model. Time series generally consists of a linear combination of trend, periodicity and stochastic component. However, when framing time series model through these data, trend and periodicity component have to be removed. Wavelet transform which is denoising technique is applied to remove nonlinear dynamic noise such as trend and periodicity included in hydrometeorological data and simple noise that arises in the measurement process. The wavelet-artificial neural network (WANN) using data applied wavelet transform as input variable and the artificial neural network (ANN) using only raw data are compared. As a results, coefficient of determination and the slope through linear regression show that WANN is higher than ANN by 0.031 and 0.0115 respectively. And RMSE and RRMSE of WANN are smaller than those of ANN by 37.388 and 0.099 respectively. Therefore, WANN model applied in this study shows more accurate results than ANN and application of denoising technique through wavelet transforms is expected that more accurate predictions than the use of raw data with noise.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.721-731
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• 2010

The rainfall-runoff relationship is very difficult to predict because it is complicate factor affected by many temporal and spatial parameters of the basin. In recent, models which is based on artificial intelligent such as neural network, genetic algorithm fuzzy etc., are frequently used to predict discharge while stochastic or deterministic or empirical models are used in the past. However, the discharge data which are generally used for prediction as training and validation set are often estimated from rating curve which has potential error in its estimation that makes a problem in reliability. Therefore, in this study, water stage is predicted from antecedent rainfall and water stage data for short term using three models of neural network which trained by error back propagation algorithm and optimized by genetic algorithm and training error back propagation after it is optimized by genetic algorithm respectively. As the result, the model optimized by Genetic Algorithm gives the best forecasting ability which is not much decreased as the forecasting time increase. Moreover, the models using stage data only as the input data give better results than the models using precipitation data with stage data.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.67-80
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• 2005

In this paper, the primary objective of the research are to review the methods currently avaliable for estimating the delay incurred by vehicles at signalized intersections. The paper compares the delay estimates from a deterministic queueing model, a model based on shock wave theory , the steady-state Webster model, the queue-based models defined in the 1994 and 2001 version of the High way Capacity Manual, in addition to the delays estimated from the TRANSYT-7F macroscopic simulation and NETSIM microscopic simulation. More especially, this paper is to compare the delay estimates obtained using macroscopic and microscopic simulation tools against state-of-the practice analytical models that are derived from deterministic queueing and shock wave analysis theory. The results of the comparisons indicate that all delay models produce relatively similar results for signalized intersections with low traffic demand, but that increasing differences occur as the traffic demand approaches saturation. In particular, when the TRANSYT-7F and NETSIM are compared, it is highly differences as approach for traffic condition to over-saturation. Also, the NETSIM microscopic simulation is the lowest estimates among the various models.

• Journal of Preventive Medicine and Public Health
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• v.22 no.4 s.28
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• pp.542-554
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• 1989

The skyrocketing inflation of medical costs has become a major health problem among most developed countries. Korea, which recently covered the entire population with National Health Insurance, is facing the same problem. The proportion of health expenditure to GNP has increased from 3% to 4.8% during the last decade. This was remarkable, if we consider the rapid economic growth during that time. A few policy analysts began to raise cost containment as an agenda, after recognizing the importance of medical cost inflation. In order to Prepare an appropriate alternative for the agenda, it is necessary to find out reasons for the cost inflation. Then, we should focus on the reasons which are controllable, and those whose control are socially desirable. This study is designed to articulate the theory of medical cost inflation through literature reviews, to find out reasons for cost inflation, by analyzing aggregated data with a deterministic model. Finally to identify determinants of changes in both medical demand and service intensity which are major reasons for cost inflation. The reasons for cost inflation are classified into cost push inflation and demand pull inflation, The former consists of increases in price and intensity of services, while the latter is made of consumer derived demand and supplier induced demand. We used a time series (1983-1987), and cross sectional (over regions) data of health insurance. The deterministic model reveals, that an increase in service intensity is a major cause of inflation in the case of inpatient care, while, more utilization, is a primary attribute in the case of physician visits. Multiple regression analysis shows that an increase in hospital beds is a leading explanatory variable for the increase in hospital care. It also reveals, that an introduction of a deductible clause, an increase in hospital beds and degree of urbanization, are statistically significant variables explaining physician visits. The results are consistent with the existing theory, The magnitude of service intensity is influenced by the level of co-payment, the proportion of old age and an increase in co-payment. In short, an increase in co-payment reduced the utilization, but it induced more intensities or services. We can conclude that the strict fee regulation or increase in the level of co-payment can not be an effective measure for cost containment under the fee for service system. Because the provider can react against the regulation by inducing more services.

• Journal of Wetlands Research
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• v.21 no.1
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• pp.16-26
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• 2019

Wetlands that provide diverse ecosystem services, such as habitat provision and hydrological control of flora and fauna, constitute ecosystems through interaction between wetlands existing in a wetlandscape. Therefore, to evaluate the wetland functions such as resilience, it is necessary to analyze the ecological connectivity that is formed between wetlands which also show hydrologically dynamic behaviors. In this study, by defining wetlands as ecological nodes, we generated ecological networks through the connection of wetlands according to the dispersal model of wetland species. The characteristics of these networks were then analyzed using various network metrics. In the case of the dispersal based on a threshold distance, while a high local clustering is observed compared to the exponential dispersal kernel and heavy-tailed dispersal model, it showed a low efficiency in the movement between wetlands. On the other hand, in the case of the stochastic dispersion model, a low local clustering with high efficiency in the movement was observed. Our results confirmed that the ecological network characteristics are completely different depending on which dispersal model is chosen, and one should be careful on selecting the appropriate model for identifying network properties which highly affect the interpretation of network structure and function.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.5
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• pp.373-381
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• 2021

This paper details the result of flight experiment that examines performance of roll angle estimation algorithm of slowly rolling munition taking time delay of measurement into account when measurement comes in delayed fashion. As the measurement is passed through low pass filter for numerical stabilization and de-noising purpose which induces time delay, we design augmented state Kalman filter that incorporates distribution models of stochastic delay over time. Flight experiment was conducted to verify the algorithm at around 250m high AGL(Above Ground Level) conveying velocity of 28m/s from fixed-wing mother plane to the munition. Munition was made spun with respect to its roll axis using internal reaction wheel afterward. Numerical comparison of proposing method's roll estimation performance with that of commercial aerospace graded GPS/INS shows that proposed filter design can effectively compensate time delay of measurement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.558-565
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• 2021

The Republic of Korea Navy has deployed naval fleets in the East, West, and South seas to effectively respond to threats from North Korea and its neighbors. However, it is difficult to allocate proper missions due to high uncertainties, such as the year of introduction for the ship, the number of mission days completed, arms capabilities, crew shift times, and the failure rate of the ship. For this reason, there is an increasing proportion of expenses, or mission alerts with high fatigue in the number of workers and traps. In this paper, we present a simulation model that can optimize the assignment of naval vessels' missions by using a continuous time absorbing Markov chain that is easy to model and that can analyze complex phenomena with varying event rates over time. A numerical analysis model allows us to determine the optimal mission durations and warship quantities to maintain the target operating rates, and we find that allocating optimal warships for each mission reduces unnecessary alerts and reduces crew fatigue and failures. This model is significant in that it can be expanded to various fields, not only for assignment of duties but also for calculation of appropriate requirements and for inventory analysis.

• Environmental and Resource Economics Review
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• v.30 no.2
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• pp.237-268
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• 2021

As variable renewable sources rapidly increase due to the Energy Transition plan, integration cost of renewable sources to the power system is rising sharply. The increase in variable renewable energy reduces the capacity factor of existing traditional power capacity, and this undermines the efficiency of the overall power supply, and demand resources are drawing attention as a solution. In this study, we analyzed how much electric vehicle demand resouces, which has great potential among other demand resources, can reduce power supply costs if it is used as a flexible resource for renewable generation. As a methodology, a stochastic form of power system optimization model that can effectively reflect the volatile characteristics of renewable generation is used to analyze the cost induced by renewable energy and the benefits offered by electric vehicle demand resources. The result shows that virtual power plant-based direct control method has higher benefits than the time-of-use tariff, and the higher the proportion of renewable energy is in the power system, the higher the benefits of electric vehicle demand resources are. The net benefit after considering commission fee for aggregators and battery wear-and-tear costs was estimated as 67% to 85% of monthly average fuel cost under virtual power plant with V2G capability, and this shows that a sufficient incentive for market participation can be offered when a rate system is applied in which these net benefits of demand resources are effectively distributed to consumers.

• Korean Journal of Optics and Photonics
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• v.31 no.6
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• pp.247-258
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• 2020

In this paper, based on a stochastic parallel gradient descent (SPGD) algorithm we study phase control of a coherent-beam-combining system under turbulent atmospheric conditions. Based on the statistical theory of atmospheric turbulence, we carry out the analysis of the phase and wavefront distortion of a laser beam propagating through a turbulent atmospheric medium. We also conduct numerical simulations of a coherent-beam-combining system with 7- and 19-channel laser beams distorted by atmospheric turbulence. Through numerical simulations, we characterize the phase-control characteristics and efficiency of the coherent-beam-combining system under various degrees of atmospheric turbulence. It is verified that the SPGD algorithm is capable of realizing 7-channel coherent beam combining with a beam-combining efficiency of more than 90%, even under the turbulent atmospheric conditions up to cn2 of 10-13 m-2/3. In the case of 19-channel coherent beam combining, it is shown that the same turbulent atmospheric conditions result in a drastic reduction of the beam-combining efficiency down to 60%, due to the elevated impact of the corresponding refractive-index inhomogeneity. In addition, by putting together the number of iterations of the SPGD algorithm required for phase locking under atmospheric turbulence and the time intervals of atmospheric phenomena, which typically are of the order of ㎲, it is estimated that hundreds of MHz to a few GHz of computing bandwidth of SPGD-based phase control may be required for a coherent-beam-combining system to confront such turbulent atmospheric conditions. We expect the results of this paper to be useful for quantitatively analyzing and predicting the effects of atmospheric turbulence on the SPGD-based phase-control performance of a coherent-beam-combining system.