• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.953-959
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• 2002

계절유행상품의 수요는 연중 성수기가 길지 않고 매년 유행과 제품디자인 변화가심한 경향이 있어 수요예측에 과거의 판매정보의 유용성이 크지 않다. 성수기 초반의 수요가 연간 수요결정에 매우 중요하며 후반부수요가 급격히 감소하는 특성이 있다. 반면 이월상품의 잔존가치가 매우 낮지만 매출마진이 높아 수요예측의 정확도에 따라 수익률이 큰 영향을 받는다. 이러한 이유로 기존의 수요예측방법을 계절상품에 적용하기에 무리가 따르며 예측오차의 비용이 매우 커서 계절상품 관리에 이용할 수 없다. 본 연구에서 성수기를 하위기간으로 구분하여 시즌 초반부 수요발생시점을 측정하여 초반부 기간별수요량을 구하고 이를 근거로 기간 누적수요비율을 quantile regression에 의거 추정하여 기간별 수요량과 전제 수요량을 예측하는 방법을 제시하고 모의자료를 사용하여 이 모형의 우수성을 평가하였다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.1956-1963
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• 2010

Studies on the development of various energy management programs and real-time bidirectional information infrastructures have been actively conducted to promote the reduction of power demands and CO2 emissions effectively. In the conventional energy management programs, the demand response program that can transition or transfer the power use spontaneously for power prices and other signals has been largely used throughout the inside and outside of the country. For measuring the effect of such demand response program, it is necessary to exactly estimate short-term loads. In this study, the power consumption patterns in both individual and group consumers were analyzed to estimate the exact short-term loads, and the relationship between the actual power consumption and seasonal factors was also analyzed.

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.2
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• pp.122-130
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• 2014

Seasonal variations and long term linear trends of SST (Sea Surface Temperature) at Yeosu Coast ($127^{\circ}37.73^{\prime}E$, $34^{\circ}37.60^{\prime}N$) in Korea were studied performing the harmonic analysis and the regression analysis of the monthly mean SST data of 46 years (1965-2010) collected by the Fisheries Research and Development Institute in Korea. The mean SST and the amplitude of annual SST variation show $15.6^{\circ}C$ and $9.0^{\circ}C$ respectively. The phase of annual SST variation is $236^{\circ}$. The maximum SST at Yeosu Coast occurs around August 26. Climatic changes in annual mean SST have had significant increasing tendency with increase rate $0.0305^{\circ}C/Year$. The warming trend in recent 30 years (1981-2010) is more pronounced than that in the last 30 years (1966-1995) and the increasing tendency of winter SST dominates that of the annual SST. The time series model that could be used to forecast the SST on a monthly basis was developed applying Box-Jenkins methodology. $ARIMA(1,0,0)(2,1,0)_{12}$ was suggested for forecasting the monthly mean SST at Yeosu Coast in Korea. Mean absolute percentage error to measure the accuracy of forecasted values was 8.3%.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.19-36
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• 2024

The global seasonal forecasting system version 6 (GloSea6) operated by the Korea Meteorological Administration for 1- and 3-month prediction products does not include complex atmospheric chemistry-aerosol physical processes (UKCA). In this study, low-resolution GloSea6 and GloSea6 coupled with UKCA (GloSea6-UKCA) were installed in a CentOS-based Linux cluster system, and preliminary prediction results for the spring of 2000 were examined. Low-resolution versions of GloSea6 and GloSea6-UKCA are highly needed to examine the effects of atmospheric chemistry-aerosol owing to the huge computational demand of the current high resolution GloSea6. The spatial distributions of the surface temperature and daily precipitation for April 2000 (obtained from the two model runs for the next 75 days, starting from March 1, 2000, 00Z) were compared with the ERA5 reanalysis data. The GloSea6-UKCA results were more similar to the ERA5 reanalysis data than the GloSea6 results. The surface air temperature and daily precipitation prediction results of GloSea6-UKCA for spring, particularly over East Asia, were improved by the inclusion of UKCA. Furthermore, compared with GloSea6, GloSea6-UKCA simulated improved temporal variations in the temperature and precipitation intensity during the model integration period that were more similar to the reanalysis data. This indicates that the coupling of atmospheric chemistry-aerosol processes in GloSea6 is crucial for improving the spring predictions over East Asia.

• Culinary science and hospitality research
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• v.15 no.2
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• pp.231-242
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• 2009

One of the most crucial information at the hotel banquet is revenue data. Revenue forecast enables cost reduction, increases staffing efficiency, and provides information that helps maximizing competitive advantages in unforeseen environment. This research forecasts the hotel banquet revenue by utilizing ARIMA Model which was assessed as the appropriate forecast model for international researches. The data used for this research was based on the monthly banquet revenue data of G hotel at Seoul. The analysis results showed that SARIMA(2, 1, 3)(0, 1, 1) was finally presumed. This research implied that the ARIMA model, which was assessed as the appropriate forecast model, was applied for analyzing the monthly hotel banquet revenue data. Additionally, the research provides beneficial information with which hotel banquet professionals can utilize as a reference.

• Atmosphere
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• v.25 no.2
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• pp.271-281
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• 2015

The objectives of this study are to develop a hydrological drought outlook system using GloSea5 (Global Seasonal forecasting system 5) which has recently been used by KMA (Korea Meteorological Association) and to evaluate the forecasting capability. For drought analysis, the bilinear interpolation method was applied to spatially downscale the low-resolution outputs of GloSea5 and PR (Predicted Runoff) was produced for different lead times (i.e., 1-, 2-, 3-month) running LSM (Land Surface Model). The behavior of PR anomaly was similar to that of HR (Historical Runoff) and the estimated values were negative up to lead times of 1- and 2-month. For the evaluation of drought outlook, SRI (Standardized Runoff Index) was selected and PR_SRI estimated using PR. ROC score was 0.83, 0.71, 0.60 for 1-, 2- and 3-month lead times, respectively. It also showed the hit rate is high and false alarm rate is low as shorter lead time. The temporal Correlation Coefficient (CC) was 0.82, 0.60, 0.31 and Root Mean Square Error (RMSE) was 0.52, 0.86, 1.20 for 1-, 2-, 3-month lead time, respectively. The accuracy of PR_SRI was high up to 1- and 2-month lead time on local regions except the Gyeonggi and Gangwon province. It can be concluded that GloSea5 has high applicability for hydrological drought outlook.

• Environmental and Resource Economics Review
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• v.21 no.3
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• pp.465-491
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• 2012

Climate change, a result of increasing global warming, has been receiving more public attention due to its serious impact upon many industries. In this study we consider sustainable- (Green-) Growth and Green-Finance, and in particular temperature derivatives, as appropriately active responses to the world's significant climate change trends. We characterize the daily average temperatures in Seoul, South Korea with their seasonal properties and cycles of error terms. We form forecasting models and perform Monte Carlo simulations, and find that the risk-neutral values for CDD call-options and HDD put-options have risen since 1960s, which implies that the trend of temperature increase can be quantified in the financial markets. Contrary to the existing models, the Vasicek model with the explicit consideration of cycles in the error terms suggests that the significant option-values for the CDD call -options above certain exercise prices, implying that there is the possibility of explicit hedging against the considerable and stable increase in temperature.

• Economic and Environmental Geology
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• v.50 no.4
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• pp.267-276
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• 2017

Seawater intrusion into coastal fractured rock aquifer, resulting in groundwater contamination, is of serious concern in coastal areas of Jeolla Namdo, Korea, which heavily depends on groundwater resources. Time series analysis and forecasting were carried out to analyze and predict EC which is a major indicator of seawater intrusion. Two time series models of autoregressive integrated moving average (ARIMA) and seasonal autoregressive integrated moving average (SARIMA) were tested for suggesting appropriate time series model. Time series data of EC measured over one year showed a increasing trend with short periodic fluctuations, due to tidal effect and pumping, which indicated that EC time series data tended to be non-stationary. SARIMA model was found better fitted to observed EC than any other time series model. Time series analysis and modeling was found to be a useful tool to analyze EC at coastal fractured rock aquifer subject to seawater intrusion.

• Journal of Korea Water Resources Association
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• v.42 no.8
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• pp.673-680
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• 2009

Alternatives to conventional water resources are being sought due to the scarcity and the poor quality of surface water. Riverbank filtration (RBF) is one of them and considered as a promising source of water supply in some cities. Changwon City has started RBF in 2001 and field data have been accumulated. This study is to develop a time-series model for groundwater level data collected from the pumping area of RBF. The site is Daesan-myeon, Changwon City, where groundwater level data have been measured for the last five years (Jan. 2003$\sim$Dec. 2007). Minute-based groundwater levels was averaged out to monthly data to see the long-term behavior. Time-series analysis was conducted according to the Box-Jenkins method. The resulted model turned out to be a seasonal ARIMA model, and its forecasting performance was satisfactory. We believe this study will provide a prototype for other riverbank filtration sites where the predictability of groundwater level is essential for the reliable supply of water.

• Journal of Environmental Science International
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• v.27 no.6
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• pp.425-436
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• 2018

To establish initial response scenarios for nuclear accidents around the Kori nuclear power plants, the potential for radionuclide diffusion was estimated using numerical experiments and statistical techniques. This study used the numerical model WRF (Weather Research and Forecasting) and FLEXPART (Flexible Particle dispersion model) to calculate the three-dimensional wind field and radionuclide dispersion, respectively. The wind patterns observed at Gijang, near the plants, and at meteorological sites in Busan, were reproduced and applied to estimates of seasonally averaged wind fields. The distribution of emitted radionuclides are strongly associated with characteristics of topography and synoptic wind patterns over nuclear power plants. Since the terrain around the power plants is complex, estimates of radionuclide distribution often produce unexpected results when wind data from different sites are used in statistical calculations. It is highly probable that in the summer and autumn, radionuclides move south-west, towards the downtown metropolitan area. This study has clear limitations in that it uses the seasonal wind field rather than the daily wind field.