• Journal of Environmental Science International
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• v.25 no.11
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• pp.1521-1530
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• 2016

As a result of dividing typhoon that affected Korean Peninsular between 1999 and 2012 into 7 types of path and entering forecast field and analysis field of RDAPS, until 36 hours from the time of forecast, it is reliable to use the forecast field of RDAPS to predict typhoon and for each typhoon path, the difference between the forecast and the analysis shows normal distribution, which is usable for weather forecast until the $36^{th}$ hour. In the $48^{th}$ hour from the time of forecast, the difference of result depending on each typhoon path increased, which was analyzed to be due to errors in the forecast. It was expected that relatively reasonable results should be shown if the $36^{th}$ hour forecast is used to predict the strength and distribution of strong wind. As a result of using Korean RAM and observing the difference of the maximum damage, reliability was secured up to 36 hours and after 48hours, it was expected that the fluctuation of results may become more severe.

• Journal of Environmental Science International
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• v.24 no.7
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• pp.865-874
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• 2015

This study was conducted to investigate the correlation between the distribution chart and input data of the predicted 3-second gust and damage cost, by using the forecast field and analysis field of Regional Data Assimilation Prediction System (RDAPS) as initial input data of Korea risk assessment model (RAM) developed in the preceding study. In this study the cases of typhoon Rusa which caused occurred great damage to the Korean peninsula was analyzed to assess the suitability of initial input data. As a result, this study has found out that the distribution chart from the forecast field and analysis field predicted from the point where the effect due to the typhoon began had similarity in both 3-second gust and damage cost with the course of time. As a result of examining the correlation, the 3-second gust had over 0.8, and it means that the forecast field and analysis field show similar results. This study has shown that utilizing the forecast field as initial input data of Korea RAM could suit the purpose of pre-disaster prevention.

• The Journal of Korean Medicine
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• v.28 no.1 s.69
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• pp.117-125
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• 2007

Objectives : This study was to assess the Traditional chinese medicine forecast subjects that had been expected to be accomplished over 20 year (1990-2010). The result will help Korea medical society to compare the status of Korean Medicine with that of Traditional Chinese Medicine and to plan for polices and studies on Korean Traditional Medicine. Methods : Assessed targets were the subjects selected by the China Academy of Chinese Medical Sciences, which are classified into 6 fields. These were assigned by the quantity of related theses. Reference source is CAJ（China academic Journal) of CNKI (China National Knowledge infrastructure). Results : 1) Forecast subject ratio by field was basic theory 31% / clinical research 17% / Chinese herbal drug 17% / acupuncture and moxa 17% / Tui-na(推拿) and Qi-gong(氣功) 9% / medical information, literature history 6%. 2) Accomplishment percentage (full accomplishment) by field was medical information, literature, history 60% / basic theory 50% / acupuncture and moxa 46% Tui-na(推拿) and Qi-gong(氣功) 38% / chinese herbal drug 25% / clinical research 23%. Conclusions : 78% of all forecast subjects were accomplished or partially accomplished. According to 'accomplishment percentage by field', while those in the medical information, literature, history field were most realized of all, those in the clinical research field were least realized.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.33-33
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• 2013

We are developing empirical space weather (solar flare, solar proton event, and geomagnetic storm) forecast models based on solar data. In this talk we will review our main results and recent progress. First, we have examined solar flare (R) occurrence probability depending on sunspot McIntosh classification, its area, and its area change. We find that sunspot area and its increase (a proxy of flux emergence) greatly enhance solar flare occurrence rates for several sunspot classes. Second, a solar proton event (S) forecast model depending on flare parameters (flare strength, duration, and longitude) as well as CME parameters (speed and angular width) has been developed. We find that solar proton event probability strongly depends on these parameters and CME speed is well correlated with solar proton flux for disk events. Third, we have developed an empirical storm (G) forecast model to predict probability and strength of a storm using halo CME - Dst storm data. For this we use storm probability maps depending on CME parameters such as speed, location, and earthward direction. We are also looking for geoeffective CME parameters such as cone model parameters and magnetic field orientation. We find that all superstorms (less than -200 nT) occurred in the western hemisphere with southward field orientations. We have a plan to set up a storm forecast method with a three-stage approach, which will make a prediction within four hours after the solar coronagraph data become available. We expect that this study will enable us to forecast the onset and strength of a geomagnetic storm a few days in advance using only CME parameters and the WSA-ENLIL model. Finally, we discuss several ongoing works for space weather applications.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.05a
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• pp.78-83
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• 2005

This article suggests an improved method for more accurate load forecast for the power system. The authors propose an improved load forecast expert system based on expert's know-how. A field manual for the load forecast can be made using proposed method. The authors expect this article could give a guidance to those who wish to be load forecast expert.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.305-310
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• 1998

This research conducted concerning measures for the influence reduction to an investigation in the structure of offshore breakwater maintenance, an evaluation, a reexamination of the forecast, and a peripheral sediment transport environment. Furthermore, it aimed at the establishment of the beach transformation forecast method based on a hydraulic model study and a numeric simulation. A good result was obtained from a hydraulic model experiment and a numeric simulation as part of the basic research. And a qualitative evaluation of the flow field around the structure became possible since a numeric simulation examined flow field characteristics.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.208-209
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• 2019

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.559-564
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• 2013

In this paper a new hybrid forecast method composed of wavelet transform and neural network is proposed to forecast the wind speed more accurately. In the field of wind energy research, accurate forecast of wind speed is a challenging task. This will influence the power system scheduling and the dynamic control of wind turbine. The wind data used here is measured at 15 minute time intervals. The performance is evaluated based on the metrics, namely, mean square error, mean absolute error, sum squared error of the proposed model and compared with the back propagation model. Simulation studies are carried out and it is reported that the proposed model outperforms the compared model based on the metrics used and conclusions were drawn appropriately.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.271-277
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• 2017

As a result of rapid industrialization, air pollutants are seriously threatening the health of the people, the forecast is becoming more and more important. In forecasting air quality, it is very important to create a reliable initial field because the initial field input to the air quality forecasting model affects the accuracy of the forecast. There are several methods for enhancing the initial field input. One of the necessary techniques is data assimilation. The number of operations and the time required for such data assimilation is exponentially increased as the forecasting area is widened and the number of observation sites increases. Therefore, as the forecast size increases, it is difficult to apply the existing sequential processing method to a field requiring fast processing speed. In this paper, we propose a method that can process Cresman's method, which is one of the data assimilation techniques, in real time using CUDA. As a result, the proposed parallel processing method using CUDA improved at least 35 times faster than the conventional sequential method and other parallel processing methods.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.90.1-90.1
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• 2011

We are developing empirical space weather (geomagnetic storms, solar proton events, and solar flares) forecast models based on solar information. These models have been set up with the concept of probabilistic forecast using historical events. Major findings can be summarized as follows. First, we present a concept of storm probability map depending on CME parameters (speed and location). Second, we suggested a new geoeffective CME parameter, earthward direction parameter, directly observable from coronagraph observations, and demonstrated its importance in terms of the forecast of geomagnetic storms. Third, the importance of solar magnetic field orientation for storm occurrence was examined. Fourth, the relationship among coronal hole-CIR-storm relationship has been investigated, Fifth, the CIR forecast based on coronal hole information is possible but the storm forecast is challenging. Sixth, a new solar proton event (flux, strength, and rise time) forecast method depending on flare parameters (flare strength, duration, and longitude) as well as CME parameter (speed, angular width, and longitude) has been suggested. Seventh, we are examining the rates and probability of solar flares depending on sunspot McIntosh classification and its area change (as a proxy of flux change). Our results show that flux emergence greatly enhances the flare probability, about two times for flare productive sunspot regions.