• 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 the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.197-208
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• 2017

The purpose of this study was to construct and test a structural equation model for college student's gambling behavior. A structured questionnaire was completed by 246 college students to analyze the relationships between perspective factors(irrational gambling belief), psychological factors(depression, anxiety), social factors(parental monitoring, parental support, friend support), self-control and gambling behavior. The moderating effects of gender, friends and family's gambling behaviors were examined. The data were analyzed using SPSS 21,0 and AMOS 20.0 programs. Self-control and psychological factors directly affected the college student's gambling behavior, while perspective factors and social factors affected it indirectly. The model fit indices of the modified model were suitable for the recommended levels. The overall study findings suggest the need to develop a gambling prevention program for college students that reinforces self-control, parental monitoring and support, and friend support while reducing irrational gambling belief, depression, and anxiety. An approach that considers gender and a development of a group counseling program for family or friends are also required.

• Journal of Energy Engineering
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• v.17 no.1
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• pp.31-37
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• 2008

At present, the target amount of demand-side management and investment cost of EE (Energy Efficiency) program, which consists of high-efficiency appliances, has been estimated simply by the diffusion function based on the real historical data in the past or last year. In the internal and external condition, the penetration amount of each appliance has been estimated by Bass diffusion model which is expressed by time and three coefficients. And enough acquisition of real historical data is necessary for reasonable estimation of coefficients. In energy efficiency, to estimate the target amount of demand-side management, the penetration amount of each appliance should be primarily forecasted by Bass diffusion model in Korea. On going programs, however, lightings, inverters, vending machine and motors have a insufficient real historical data which is a essential condition to forecast the penetration amount using a Bass diffusion model due to the short period of program progress. In other words, the forecast of penetration amount may not be exact, so that it is necessary for the method of forecast to apply improvement of method. In this paper, the penetration amount of high-efficiency appliances is forecasted by Bass, virtual Bass, Logistic and Lawrence & Lawton diffusion models to analyze the diffusion progress. And also, by statistic standards, each penetration is compared with historical data for model suitability by characteristic of each appliance. Based on the these result, in the forecast of penetration amount by diffusion model, the reason for error occurrence caused by simple application of diffusion model and preferences of each diffusion model far a characteristic of data are analyzed.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.547-565
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• 2011

Different types of schemes have been used in stage prediction involving conceptual and physical models. Nevertheless, none of these schemes can be considered as a single superior model. To overcome disadvantages of existing physics based rainfall-runoff models for stage predicting because of the complexity of the hydrological process, recently the data-derived models has been widely adopted for predicting flood stage. The objective of this study is to evaluate model performance for stage prediction of the Neuro-Fuzzy and regression analysis stage prediction models in these data-derived methods. The proposed models are applied to the Wangsukcheon in Han river watershed. To evaluate the performance of the proposed models, fours statistical indices were used, namely; Root mean square error(RMSE), Nash Sutcliffe efficiency coefficient(NSEC), mean absolute error(MAE), adjusted coefficient of determination($R^{*2}$). The results show that the Neuro-Fuzzy stage prediction model can carry out the river flood stage prediction more accurately than the regression analysis stage prediction model. This study can greatly contribute to the construction of a high accuracy flood information system that secure lead time in medium and small streams.

• Convergence Security Journal
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• v.16 no.6_1
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• pp.75-83
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• 2016

Soldiers management is the core of military combat power to preserve and accident prevention. But in unforeseen times and places did the unthinkable soldier causes an accident, the inexperienced primary officer were upset, and can often be quite nervous. And various accidents prevention is also win the war, the reason for existence in the military for combat readiness as a precondition for perfection. There are primary officers at the forefront of this critical mission. However, in spite of the lack of time to work for combat readiness, orders from higher units of troops management and that's level giving a lot of pressure to primary officer. So I made the primary officer military counseling model ike this. Using Primary officer counseling model is possible to rapid and efficient counseling advice against the target client soldier. The efficient counseling is must take precedence on understanding on client soldier deeply. Depth understanding someone needs a lot of effort and time. However, to Primary officer, it is true that they have a lack of condition that are enough to give the time and effort. Therefore, effective counseling and accident prevention is possible to use counseling model through choice and concentration activities.

• Journal of the Korean Geosynthetics Society
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• v.23 no.3
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• pp.1-14
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• 2024

To better prepare for the increasing frequency of earthquakes, securing the seismic performance of coastal structures is more urgent than ever. Evaluating the stability of coastal structures precedes ensuring seismic performance. Methods for assessing stability during earthquakes include finite element analysis and model testing. However, these methods have the disadvantage of requiring significant cost and time. Therefore, this study aimed to propose a simplified method for quickly and easily predicting the horizontal displacement of caisson-type qual wall structures during earthquakes. Initially, existing simplified methods were compared and analyzed against numerical analysis. The results revealed limitations in predicting the displacement of caisson-type qual wall using existing simplified methods. To address this, correction coefficients related to the backfilled ground N value, velocity's PSI, and the W/H ratio were added to the existing simplified method. After the adjustments, a noticeable reduction in errors was observed, demonstrating high precision within the 200 gal range.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.164-173
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• 2017

Alternative cropping systems would be one of climate change adaptation options. Suitable areas for a crop could be identified using a climate suitability model. The EcoCrop model has been used to assess climate suitability of crops using monthly climate surfaces, e.g., the digital climate map at high spatial resolution. Still, a high-performance computing approach would be needed for assessment of climate suitability to take into account a complex terrain in Korea, which requires considerably large climate data sets. The objectives of this study were to implement a script for R, which is an open source statistics analysis platform, in order to use the EcoCrop model under a parallel computing environment and to assess climate suitability of maize using digital climate maps at high spatial resolution, e.g., 1 km. The total running time reduced as the number of CPU (Central Processing Unit) core increased although the speedup with increasing number of CPU cores was not linear. For example, the wall clock time for assessing climate suitability index at 1 km spatial resolution reduced by 90% with 16 CPU cores. However, it took about 1.5 time to compute climate suitability index compared with a theoretical time for the given number of CPU. Implementation of climate suitability assessment system based on the MPI (Message Passing Interface) would allow support for the digital climate map at ultra-high spatial resolution, e.g., 30m, which would help site-specific design of cropping system for climate change adaptation.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.51-65
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• 2010

We suggest a simple and practical flood forecasting and warning system, which can predict change in the water level of a river in a small to medium-size watershed where flash flooding occurs in a short time. We first choose the flood defense target points, through evaluation of the flood risk of dike overflow and lowland inundation. Using data on rainfall, and on the water levels at the observed and prediction points, we investigate the interrelations and derive a regression formula from which we can predict the flood level at the target points. We calculate flood water levels through a calibrated flood simulation model for various rainfall scenarios, to overcome the shortage of real water stage data, and these results as basic population data are used to derive a regression formula. The values calculated from the regression formula are modified by the weather condition factor, and the system can finally predict the flood stages at the target points for every leading time. We also investigate the applicability of the prediction procedure for real flood events of the Jungnang Stream basin, and find the forecasting values to have close agreement with the surveyed data. We therefore expect that this suggested warning scheme could contribute usefully to the setting up of a flood forecasting and warning system for a small to medium-size river basin.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.981-992
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• 2023

Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.

• Journal of Korea Game Society
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• v.10 no.2
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• pp.67-80
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• 2010

Investigating the trend of online gamers plays an important role in forecasting, marketing and making policy decision in gaming industry. In this regards, various studies on gamers' trend and characteristics have been conducted. However, these precedent studies show limitation that they're static analysis since they are usually based on the surveys at a certain point. Therefore, this paper aims to identify some implications on forthcoming directions of gaming industry by analyzing dynamic trend of gamers based on the 8 years(from 2002 to 2009) of data from White Paper on Korean Games. Major implications found in this paper are as follows. Negative perception of games increases as the number of gamers increases. Among juveniles, games became a substitute for TV and the amount of time they play games depends on the existence and type of popular games of that time. Also, most item trading is intensively done by a small number of gamers.