• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 정기총회 및 창립40주년기념 학술대회 학회본부
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• pp.316-320
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• 1987

This paper deals with expert system for power system fault restoration and accompanying numerical data processing. Nowadays, expert system which is a branch or artificial intelligence expands its application area to many fields. And it requires computer language for A.I. to be versatile. Expert system for power system handles numerous numerical data and language for A.I. has its deficiency in numerical data processing. However some recent version of the A.I. language rind ways of overcoming this dilemma by giving the way or linking conventional algorithmic languages to them. This study presents numerical data processing routines described in Turbo prolog which is run in IBM PC and linking numerical data processing routines written in Turbo C to Turbo prolog.

• 한국대기환경학회지
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• 제23권6호
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• pp.653-665
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• 2007

Several numerical experiments were carried out to clarify the influence of satellite data assimilation with various spatial resolution on mesoscale meteorological wind and temperature field. Satellite data used in this study is QuikSCAT launched on ADEOS II. QuikSCAT data is reasonable and faithful sea wind data, which have been verified through many observational studies. And numerical model in the study is MM5 developed by NCAR. Difference of wind pattern with and without satellite data assimilation appeared clearly, especially wind speed dramatically reduced on East Sea, when satellite data assimilation worked. And sea breeze is stronger in numerical experiments with RDAPS and satellite data assimilation than that with CDAS and data assimilation. This caused the lower estimated surface temperature in CDAS used cases. Therefore the influence of satellite data assimilation acts differently according to initial data quality. And it is necessary to make attention careful to handle the initial data for numerical simulations.

• Structural Engineering and Mechanics
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• 제29권5호
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• pp.469-488
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• 2008

Finite element methods have often been used for structural analyses of various mechanical problems. When finite element analyses are utilized to resolve mechanical systems, numerical uncertainties in the initial data such as structural parameters and loading conditions may result in uncertainties in the structural responses. Therefore the initial data have to be as accurate as possible in order to obtain reliable structural analysis results. The typical finite element method may not properly represent discrete systems when using uncertain data, since all input data of material properties and applied loads are defined by nominal values. An interval finite element analysis, which uses the interval arithmetic as introduced by Moore (1966) is proposed as a non-stochastic method in this study and serves a new numerical tool for evaluating the uncertainties of the initial data in structural analyses. According to this method, the element stiffness matrix includes interval terms of the lower and upper bounds of the structural parameters, and interval change functions are devised. Numerical uncertainties in the initial data are described as a tolerance error and tree graphs of uncertain data are constructed by numerical uncertainty combinations of each parameter. The structural responses calculated by all uncertainty cases can be easily estimated so that structural safety can be included in the design. Numerical applications of truss and frame structures demonstrate the efficiency of the present method with respect to numerical analyses of structural uncertainties.

• 대기
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• 제34권1호
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• pp.23-34
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• 2024

The Korea Meteorological Administration has improved medium-range weather forecasts by implementing post-processing methods to minimize numerical model errors. In this study, we employ a statistical correction technique known as the minimum continuous ranked probability score (CRPS) to refine medium-range forecast guidance. This technique quantifies the similarity between the predicted values and the observed cumulative distribution function of the Unified Model Ensemble Prediction System for Global (UM EPSG). We evaluated the performance of the medium-range forecast guidance for surface air temperature and relative humidity, noting significant enhancements in seasonal bias and root mean squared error compared to observations. Notably, compared to the existing the medium-range forecast guidance, temperature forecasts exhibit 17.5% improvement in summer and 21.5% improvement in winter. Humidity forecasts also show 12% improvement in summer and 23% improvement in winter. The results indicate that utilizing the minimum CRPS for medium-range forecast guidance provide more reliable and improved performance than UM EPSG.

• 한국환경과학회지
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• 제15권12호
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• pp.1141-1154
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• 2006

Orographic effect is one of the important factors to induce Local circulations and to make atmospheric turbulence, so it is necessary to use the exact topographic data for prediction of local circulations. In order to clarify the sensitivity of the spatial resolution of topography data, numerical simulations using several topography data with different spatial resolution are carried out under stable and unstable synoptic conditions. The results are as follows: 1) Influence of topographic data resolution on local circulation tends to be stronger at simulation with fine grid than that with coarse grid. 2) The hight of mountains in numerical model become mote reasonable with high resolution topographic data, so the orographic effect is also emphasized and clarified when the topographic data resolution is higher. 2) The higher the topographic resolution is, the stronger the mountain effect is. When used topographic data resolution become fine, topography in numerical model becomes closer to real topography. 3) The topographic effect tends to be stronger when atmospheric stability is strong stable. 4) Although spatial resolution of topographic data is not fundamental factor for dramatic improvement of weather prediction accuracy, some influence on small scale circulation can be recognized, especially in fluid dynamic simulation.

• 대기
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• 제31권3호
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• pp.251-265
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• 2021

This study examined the impact of assimilating the bending angle (BA) obtained via the global navigation satellite system radio occultation (GNSS RO) of the three new satellites (KOMPSAT-5, FY-3C, and FY-3D) on analyses and forecasts of a numerical weather prediction model. Numerical data assimilation experiments were performed using a three-dimensional variational data assimilation system in the Korean Integrated Model (KIM) at a 25-km horizontal resolution for August 2019. Three experiments were designed to select the height and quality control thresholds using the data. A comparison of the data with an analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) integrated forecast system showed a clear positive impact of BA assimilation in the Southern Hemisphere tropospheric temperature and stratospheric wind compared with that without the assimilation of the three new satellites. The impact of new data in the upper atmosphere was compared with observations using the infrared atmospheric sounding interferometer (IASI). Overall, high volume GNSS RO data helps reduce the RMSE quantitatively in analytical and predictive fields. The analysis and forecasting performance of the upper temperature and wind were improved in the Southern and Northern Hemispheres.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권2호
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• pp.98-104
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• 2014

Locality-sensitive hashing techniques have been developed to efficiently handle nearest neighbor searches and similar pair identification problems for large volumes of high-dimensional data. This study proposes a locality-sensitive hashing method that can be applied to nearest neighbor search problems for data sets containing both numerical and categorical attributes. The proposed method makes use of dual hashing functions, where one function is dedicated to numerical attributes and the other to categorical attributes. The method consists of creating indexing structures for each of the dual hashing functions, gathering and combining the candidates sets, and thoroughly examining them to determine the nearest ones. The proposed method is examined for a few synthetic data sets, and results show that it improves performance in cases of large amounts of data with both numerical and categorical attributes.

• 한국해안·해양공학회논문집
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• 제31권3호
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• pp.146-157
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• 2019

최근 해양예보/재해 등의 주요 분야에서 해양수치모델의 수행 및 연구결과에 대한 활용도가 증가함에 따라 정확도 높은 수심자료의 중요성이 크게 부각되고 있다. 해양수치모델에 주로 활용되는 국내 수심자료는 Choi et al.(2002), Seo(2008)의 자료가 있지만, 제작년도가 오래되고 해도를 기반으로 작성했다는 제한사항이 있다. 해도는 항해를 목적으로 제작되어 수심 측량자료 중 최천소 자료를 사용하므로 실제 해저지형을 재현하는데 한계가 있다. 국립해양조사원은 매년 지속적인 수심측량을 통하여 해도를 생산하고 있지만, 수치모델을 목적으로 한 수심자료는 생산하지 않았다. 본 연구에서는 원시 수심측량자료를 이용하여 수치모델을 위한 해양수치모델 전용 수심 데이터셋(BADA Ver.1)을 구축하고, 공개된 해양 수심자료와 비교하였다.

• 대기
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• 제33권1호
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• pp.33-47
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• 2023

In this study, for the application of observation errors to the Korean Integrated Model (KIM) to utilize the Constellation Observing System for Meteorology, Ionosphere & Climate-2 (COSMIC-2) new satellites, the observation errors were diagnosed based on the Desroziers method using the cost function in the process of variational data assimilation. We calculated observation errors for all observational species being utilized for KIM and compared with their relative values. The observation error of the calculated the Global Navigation Satellite System Radio Occultation (GNSS RO) was about six times smaller than that of other satellites. In order to balance with other satellites, we conducted two experiments in which the GNSS RO data expanded by about twice the observation error. The performance of the analysis field was significantly improved in the tropics, where the COSMIC-2 data are more available, and in the Southern Hemisphere, where the influence of GNSS RO data is significantly greater. In particular, the prediction performance of the Southern Hemisphere was improved by doubling the observation error in global region, rather than doubling the COSMIC-2 data only in areas with high density, which seems to have been balanced with other observations.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2009년도 춘계학술대회 논문집
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• pp.529-531
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• 2009

To construct the wind map for mainland Korea, the well designed atmospheric numerical modeling system was used. Three nest domains were construced with spatial resolutions between $10{\times}10km$ up to the hightest resolution of $1{\times}1km$. Parameterization schemes like MRF(PBL), RRTM(radiation), Grell(cumulus) were chosen since wind data simulated is in better agreement with the observed wind data. High-resolution atmospheric numerical model was applied to simulate the motion of the atmosphere and to produce the wind map around the South Korea. The results of several simulations were improved compare to the past system, because of using the fine geographical data, such as terrain height and land-use data, and the meteorological data assimilation.