• Journal of the Korean Geographical Society
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• v.33 no.2
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• pp.293-308
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• 1998

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.79-87
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• 2017

The microphysical processes of the numerical weather prediction (NWP) model cover the following : fall speed, accretion, autoconversion, droplet size distribution, etc. However, the microphysical processes and parameters have a significant degree of uncertainty. Parameter estimation was generally used to reduce errors in NWP models associated with uncertainty. In this study, the micro- genetic algorithm and harmony search algorithm were used as an optimization algorithm for estimating parameters. And we estimate parameters of microphysics for the Unified model in the case of precipitation in Korea. The differences which occurred during the optimization process were due to different characteristics of the two algorithms. The micro-genetic algorithm converged to about 1.033 after 440 times. The harmony search algorithm converged to about 1.031 after 60 times. It shows that the harmony search algorithm estimated optimal parameters more quickly than the micro-genetic algorithm. Therefore, if you need to search for the optimal parameter within a faster time in the NWP model optimization problem with large calculation cost, the harmony search algorithm is more suitable.

• The Journal of the Acoustical Society of Korea
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• v.39 no.1
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• pp.32-37
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• 2020

This paper proposes a new l₁-norm-Recursive Least Squares (RLS) algorithm which is numerically more robust than the conventional l₁-norm-RLS. The l₁-norm-RLS was proposed by Eksioglu and Tanc in order to estimate the sparse acoustic channel. However the algorithm has numerical instability in the inverse matrix calculation. In this paper, we propose a new algorithm which is robust against the numerical instability. We show that the proposed method improves stability under several numerically erroneous situations.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.802-803
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• 2008

본 연구에서는 변압기의 권선간 전계 및 절연안전율 예측알고리즘을 개발하였으며, 이를 활용하여 극초고압 변압기의 절연구조개선 연구를 수행하였다. 개발된 알고리즘을 사용하면 한 번의 기본모델의 수치해석 결과만을 이용하여 다양한 권선간 거리 및 고체절연물의 개수 변화에 따른 전계 및 절연안전율의 예측이 가능하다. 본 알고리즘을 극초고압 변압기 주권선부 개선에 적용시킨 결과, 권선간 고체 절연물 개수를 조절하면 절연신뢰성 저하없이 주권선부 거리를 단축시킬 수 있음을 확인하였다. 또한, 본 예측 알고리즘의 활용가능성을 검증하고자 개선 모델의 절연안전율을 수치해석적 방법으로 계산하여 이를 예측 결과와 비교하였다. 그 결과, 본 예측 알고리즘으로 계산된 결과는 수치해석적 방법에 의한 결과에 비해 약 $1{\sim}2%$ 정도의 작은 차이가 발생하는 것으로 확인되었다. 따라서 본 연구를 통하여 개발된 전계분포 및 절연안전율 예측기법을 실제 설계에 적용할 수 있을 것으로 판단된다.

• Tunnel and Underground Space
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• v.18 no.3
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• pp.202-213
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• 2008

In this study, theoretical approach of 3D seismic traveltime tomography was investigated. To guarantee the successful field application of 3D tomography, appropriate control of problem associated with blind zone is pre-requisite. To overcome the velocity distortion of the reconstructed tomogram due to insufficient source-receiver array coverage, the algorithm of 3D seismic traveltime tomography based on the Fresnel volume was developed as a technique of ray-path broadening. For the successful reconstruction of velocity cube, 3D traveltime algorithm was explored and employed on the basis of 2nd order Fast Marching Method(FMM), resulting in improvement of precision and accuracy. To prove the validity and field application of this algorithm, two numerical experiments were performed for globular and layered models. The algorithm was also found to be successfully applicable to field data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.595-601
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• 2018

Recently, as the fine dust level has risen rapidly, there is a great interest. Exposure to fine dust is associated with the development of respiratory and cardiovascular diseases and has been reported to increase death rate. In addition, there exist damage to fine dusts continues at industrial sites. However, exposure to fine dust is inevitable in modern life. Therefore, predicting and minimizing exposure to fine dust is the most efficient way to reduce health and industrial damages. Existing fine dust prediction model is estimated as good, normal, poor, and very bad, depending on the concentration range of the fine dust rather than the concentration value. In this paper, we study and implement to predict the PM10 level by applying the Artificial neural network algorithm and the K-Nearest Neighbor algorithm, which are machine learning algorithms, using the actual weather and air quality data.

• The Journal of the Acoustical Society of Korea
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• v.40 no.3
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• pp.213-218
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• 2021

It is known that total least-squares method shows better estimation performance than least-squares method when noise is present at the input and output at the same time. When total least squares method is applied to data with time series characteristics, Recursive Total Least Squares (RTS) algorithm has been proposed to improve the real-time performance. However, RTLS has numerical instability in calculating the inverse matrix. In this paper, we propose an algorithm for reducing numerical instability as well as having similar convergence to RTLS. For this algorithm, we propose a new RTLS using Iterative Wiener Filter (IWF). Through the simulation, it is shown that the convergence of the proposed algorithm is similar to that of the RTLS, and the numerical robustness is superior to the RTLS.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.45-52
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• 2015

The interoperability of multi-source data has become more important due to various digital maps, produced from public institutions and enterprises. In this study, the automatic matching algorithm of multi-source building data using hierarchical matching was proposed. At first, we divide digital maps into blocks and perform the primary geometric registration of buildings with the ICP algorithm. Then, corresponding building pairs were determined by evaluating the similarity of overlap area, and the matching threshold value of similarity was automatically derived by the Otsu binary thresholding. After the first matching, we extracted error matching candidates buildings which are similar with threshold value to conduct the secondary ICP matching and to make a matching decision using turning angle function analysis. For the evaluation, the proposed method was applied to representative public digital maps, road name address map and digital topographic map 2.0. As a result, the F measures of matching and non-matching buildings increased by 2% and 17%, respectively. Therefore, the proposed method is efficient for the matching of building polygons from multi-source digital maps.

• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.121-132
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• 1997

This paper describes the development of a stereo matching algorithm for extracting Digital Elevation Model(DEM) from satellite images. This matching algorithm is based on a non-linear least squares correlation estimation but has improved matching speed. The algorithm consists of three steps: matching execution, matching control and matching optimization. Each is described. The performance of the presented algorithm is quantitatively analyzed with experiments on matching probability, matching speed and matching convergence radius.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.291-298
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• 1996

통계학분야 그리고 또 다른 많은 분야에서 수치적 계산을 다루는 문제가 자주 발생한다. 적당한 컴퓨터 컴퓨터 시간안에 상당한 정도의 정확성을 줄 수 있고 또한 보다 광범위하게 사용 가능한 유용한 알고리즘의 필요성을 느낀다. 이러한 문제에 가능한 하나의 몬테칼로 알고리즘인 주표본 알고리즘을 소개하였다. 그리고 특히 본 눈문에서는 축차확률비검정의 오차확률을 계산하는 곳에 주표본 알고리즘을 적용하고 결과를 비교분석하였다.