• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.164.1-164.1
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• 2011

Previously, many researchers assessed nearshore wave energy in two ways. The first is a simulation with respect to the offshore wave time series to validate the wave buoy data and the wave model results, and the other is to simulate the representative waves of typical seasonal wave conditions. The former requires enormous computational time and effort. The latter yields inspection on the patterns for the spatial and temporal distribution of nearshore wave energy but tends to underestimates the amount of wave energy in the nearshore region owing to the correlation between the significant wave height and wave period. $\ddot{O}$zger et al. (2004) derived the stochastic wave energy formulation by introducing a correction factor explicitly in terms of the covariance of the wave energy and significant wave height. In this study, a correction factor was applied for the assessment of nearshore wave energy obtained by numerical simulation of wave transformation with respect to representative waves.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.143-148
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• 2005

The main purpose of this study is to suggest and evaluate an operational method for assessing the potential impact of climate change on hydrologic components and water resources of regional scale river basins. The method, which uses large scale climate change information provided by a state of the art general circulation model(GCM) comprises a statistical downscaling approach and a spatially distributed hydrological model applied to a river basin located in Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about $7.6\% of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern and the analysis of the duration cure shows the mean of averaged low flow is increased while the averaged wet and normal flow are decreased for the climate change.

• Atmosphere
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• v.31 no.2
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• pp.215-227
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• 2021

The necessity of the prediction on the Seasonal-to-Subseasonal (S2S) timescale continues to rise. It led a series of studies on the S2S prediction models, including the Global Seasonal Forecasting System Version 5 (GloSea5) of the Korea Meteorological Administration. By extending previous studies, the present study documents sea surface temperature (SST) prediction skill around the Korean peninsula in the GloSea5 hindcast over the period of 1991~2010. The overall SST prediction skill is about a week except for the regions where SST is not well captured at the initialized date. This limited prediction skill is partly due to the model mean biases which vary substantially from season to season. When such biases are systematically removed on daily and seasonal time scales the SST prediction skill is improved to 15 days. This improvement is mostly due to the reduced error associated with internal SST variability during model integrations. This result suggests that SST around the Korean peninsula can be reliably predicted with appropriate post-processing.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1511-1523
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• 2016

The increasing trend of the five violent crimes (murder, robbery, rape, violence, theft) in Korea is not independent of social and economic factors. Several social science research have discussed about this issue but most of them do not properly reflect the nature of the time-series data. Based on several time series models, we studied about the endogenous factors (time, seasonal and cycle factors) and exogenous factors (economical, social change and crime control factors) on violent crime occur in Korea. Autocorrelation were also taken into account. Through this study, we want to help to make preventive policy by explaining the cause of violent crime and predicting the future incidence of it.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.183-188
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• 2001

The NOAA AVHRR remotely sensed SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the sea near korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple SST images, all of images must be consistent exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which automatically detects cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$3$^{\circ}C$ as a criterion of SST anomalies). The remotely sensed SST data are tuned by comparing remotely sensed data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel and the SST anomalies are studied by statistical method. It was found that the SST anomalies are rather persistent for one or two months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST. In the Markov lprocess model of SST anomalies, autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. The developed algorithm with automatic cloud pixel detection and rediction of future SST is expected to be incorporated to the operational real time service of SST around Korea.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.185-193
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• 2004

The main purpose of this study is to investigate and evaluate the impact of climate change on the runoff and water resources of Yongdam basin. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONV GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about 7.6％ of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.6
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• pp.617-623
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• 2001

To predict the seasonal variation of dissolved oxygen (DO) in Hakata bay, Japan, possible 20 time-series of different hourly-solar-radiation intensities were generated based on stochastically changing solar radiation intensity, and a numerical simulation on dissolved oxygen (DO) was carried out for each time series by using the Sediment-Water Ecological Model (SWEM). The model, consisting of two sub-models with hydrodynamic and biological models, simulates the circulation process of nutrient between water column and sediment, such as nutrient regeneration from sediments as well as ecological structures on the growth of phytoplankton and zooplankton, The results of the model calibration followed the seasonal variation of observed water quality well, and generated cumulative-frequency-distribution (CFD) curves of daily solar radiation agreed well with observed ones, The simulation results indicated that the exchange of sea water would have a great influence on the DO concentration, and that the concentration could change more than 1 mg/L in a day. This prediction method seems to be an effective way to examine a solution to minimize fishery damage when DO is depleted.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.335-350
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• 1998

X11ARIMA is established on the basis of X11 which is one of smoothing approach in time series area and this procedure was introduced by Bureau of Census of United States and developed by Dagum(1975). This procedure had been updated and adjusted by Dagum(1988) with 174 economic index of North America and has been used until nowadays. Recently, X12ARIMA procedure has been studied by William Bell et.al. (1995) and Chen. & Findly(1995) whose approaches adapt adjusting outliers, Trend-change effects, seasonal effect, arid Calender effect. However, both of these procedures were implemented for correct adjusting the economic index of North America. This article starts with providing some appropriate and effective ARIMA model for 102 indexes produced by national statistical office in Korea; which consists of production(21), shipping(27), stock(27), and operating rate index(21). And a reasonable smoothing method will be proposed to reflect the specificity of Korean economy using several moving average model. In addition, Sulnal(lunar happy new year) and Chusuk effects will be extracted from the indexes above and both of effects reflect contribution of lunar calender effect. Finally, we will discuss an alternative way to estimate holiday effect which is similar to X12ARIMA procedure in concept of using both of ARIMA model and Regression model for the best fitness.

• Asian Journal of Business Environment
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• v.7 no.4
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• pp.35-41
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• 2017

Purpose - This paper aims to examine several time series models to predict sales of department stores and discount store markets in South Korea, while other previous trial has performed sales of convenience stores and supermarkets. In addition, optimal predicted values on the underlying model can be got and be applied to distribution industry. Research design, data, and methodology - Two retailing types, under investigation, are homogeneous and comparable in size based on 86 realizations sampled from January 2010 to February in 2017. To accomplish the purpose of this research, both ARIMA model and exponential smoothing methods are, simultaneously, utilized. Furthermore, model-fit measures may be exploited as important tools of the optimal model-building. Results - By applying Holt-Winters' additive seasonality method to sales of two large-scale retailing types, persisting increasing trend and fluctuation around the constant level with seasonal pattern, respectively, will be predicted from May in 2017 to February in 2018. Conclusions - Considering 2017-2018 forecasts for sales of two large-scale retailing types, it is important to predict future sales magnitude and to produce the useful information for reforming financial conditions and related policies, so that the impacts of any marketing or management scheme can be compared against the do-nothing scenario.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.299-303
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• 2008

In this study, an uncertainty assessment for surface air temperature(T2m) and precipitation(PCP) over East Asia is carried out. The data simulated by the intergovermental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) Atmosphere-Ocean coupled general circulation Model (AOGCM) are used to assess the uncertainty. Examination of the seasonal uncertainty of T2m and PCP variabilities shows that spring-summer cold bias and fall warm bias of T2m are found over both East Asia and the Korea peninsula. In contrast, distinctly summer dry bias and winter-spring wet bias of PCP over the Korea peninsula is found. To investigate the PCP seasonal variability over East Asia, the cyclostationary empirical orthogonal function(CSEOF) analysis is employed. The CSEOF analysis can extract physical modes (spatio-temporal patterns) and their undulation (PC time series) of PCP, showing the evolution of PCP. A comparison between spatio-temporal patterns of observed and modeled PCP anomalies shows that positive PCP anomalies located in northeastern China (north of Korea) of the multi-model ensemble(MME) cannot explain properly the contribution to summer monsoon rainfalls across Korea and Japan. The uncertainty of modeled PCP indicates that there is disagreement between observed and MME anomalies. The spatio-temporal deviation of the PCP is significantly associated with lower- and upper-level circulations. In particular, lower-level moisture transports from the warm pool of the western Pacific and corresponding moisture convergence significantly contribute to summer rainfalls. These lower- and upper-level circulations physically consistent with PCP give a insight of the reason why differences between modeled and observed PCP occur.