• Journal of the Korean Geotechnical Society
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• v.26 no.5
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• pp.57-64
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• 2010

Kriging techniques have been used to estimate the spatial distribution of soil layers and soil properties in the geotechnical engineering area. Since the selected kriging technique may provide different values of estimation, the selection of method is important in the geotechnical estimation. In this paper, the spatial distribution of the thickness of consolidation layer of Songdo International City is estimated using simple, ordinary, and universal kriging techniques, and the reliability of estimated results is analyzed. It is shown that the consolidation layer thickness estimated by the simple kriging technique is larger than those by other kriging techniques when the location of estimation is far from the locations where the measured data exist. In this case, the reliability of the simple kriging technique is observed to be lower than those of other techniques. Universal kriging gives a negative value for thickness of consolidation layer in some locations away from the data. It is concluded that the ordinary kriging is the most optimized estimation technique because the reliability of ordinary kriging technique is higher than those of other ones and the consolidation layer thickness estimated by the ordinary kriging locates within the reasonable range.

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.271-280
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• 2005

Kriging methods as traditional spatial data analysis methods and geographical weighted regression models as statistical analysis methods are compared. In this paper, we apply data from the Ministry of Environment to spatial analysis for practical study. We compare these methods to performance with monthly carbon monoxide observations taken at 116 measuring area of air pollution in 1999.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.133-133
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• 2018

최근 기후변화로 인해 국지성 호우와 도시화로 인한 불투수율 증가로 내수침수 및 홍수와 같은 피해가 빈번하게 발생하고 있는 추세이다. 이로 인해 강우 관측의 정확도에 대한 논의가 지속되고 있으며, 공간적 분포를 고려할 수 있는 레이더의 활용성이 증가하고 있다. 하지만 레이더 자료는 지상강우 자료와 달리, 반사도와 강우강도 간에 관계식(Z-R 관계식)을 통한 추정치이기 때문에 실제 관측한 지상강우 자료와 함께 보정작업을 수행해야 한다. 본 연구에서는 지구통계학분야에서 제시된 공간 보간법중 하나인 크리깅 기법을 이용하여 강우의 공간적 분포를 추정하였다. 본 연구에서 사용한 크리깅 기법으로는 일반적으로 많이 사용되는 OK(Ordinary Kriging), CK(Co-Kriging), KED(Kriging with External Drift)와 RK(Regression Kriging)기법을 사용하였고, 이를 이용하여 강우장을 생성하고, 생성된 강우장과 레이더값을 비교하였다. 지상강우와 관측소 위치에서의 실제 강우값과 추정된 강우값의 정량적 평가를 실시하였으며, 레이더 강우자료의 공간분포특성과 유사성을 확인하기 위해 각 기법에서의 베리오그램을 비교하였다. 본 연구를 통해 공간적 분포를 고려하여 강우장 분포의 정확도를 높일 수 있었고, 향후 다양한 레이더 보정기법과의 비교를 통해 강우 관측의 정확도를 높일 수 있을 것으로 판단된다.

• Journal of Wetlands Research
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• v.17 no.4
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• pp.370-379
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• 2015

In recent, the natural disaster like localized heavy rainfall due to the climate change is increasing. Therefore, it is important issue that the precise observation of rainfall and accurate spatial distribution of the rainfall for fast recovery of damaged region. Thus, researches on the use of the radar rainfall data have been performed. But there is a limitation in the estimation of spatial distribution of rainfall using rain gauge. Accordingly, this study uses the Kriging method which is a spatial interpolation method, to measure the rainfall field in Namgang river dam basin. The purpose of this study is to apply KED(Kriging with External Drift) with OK(Ordinary Kriging) and CK(Co-Kriging), generally used in Korea, to estimate rainfall field and compare each method for evaluate the applicability of each method. As a result of the quantitative assessment, the OK method using the raingauge only has 0.978 of correlation coefficient, 0.915 of slope best-fit line, and 0.957 of $R^2$ and shows an excellent result that MAE, RMSE, MSSE, and MRE are the closest to zero. Then KED and CK are in order of their good results. But the quantitative assessment alone has limitations in the evaluation of the methods for the precise estimation of the spatial distribution of rainfall. Thus, it is considered that there is a need to application of more sophisticated methods which can quantify the spatial distribution and this can be used to compare the similarity of rainfall field.

• Proceedings of the Korea Water Resources Association Conference
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• 1992.07a
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• pp.256-263
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• 1992

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.380-388
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• 2014

Annual average daily traffic(AADT) serves as important basic data in the transportation sector. AADT is used as design traffic which is the basic traffic volume in transportation planning. Despite of its importance, at most locations, AADT is estimated using short term traffic counts. An accurate AADT is calculated through permanent traffic counts at limited locations. This study dealt with estimating AADT using various models considering both the spatial correlation and time series data. Kriging models which are commonly used spatial statistics methods were applied and compared with each model. Additionally the External Universal kriging model, which includes explanatory variables, was used to assure accuracy of AADT estimation. For evaluation of various kriging methods, AADT estimation error, proposed using national highway permanent traffic count data, was analyzed and their performances were compared. The result shows the accuracy enhancement of the AADT estimation.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.471-477
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• 2014

The novel permanent magnetic actuator (PMA) and its optimal design method were proposed in this paper. The proposed PMA is referred to as the separated permanent magnetic actuator (SPMA) and significantly superior in terms of its cost and performance level over a conventional PMA. The proposed optimal design method uses the evolutionary strategy algorithm (ESA), the kriging meta-model (KMM), and the multi-step optimization. The KMM can compensate the slow convergence of the ESA. The proposed multi-step optimization process, which separates the independent variables, can decrease time and increase the reliability for the optimal design result. Briefly, the optimization time and the poor reliability of the optimum are mitigated by the proposed optimization method.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.28-36
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• 2007

A multi-objective design exploration for a three-element airfoil consisted of a slat, a main wing, and a flap was carried out. The lift curve improvement is important to design high-lift system, thus design has to be performed with considered multi-angle. The objective functions considered here are to maximize the lift coefficient at landing and near stall conditions simultaneously. Kriging surrogate model which was constructed based on several sample designs is introduced. The solution space was explored based on the maximization of Expected Improvement (EI) value corresponding to objective functions on the Krigingmodels. The improvement of the model and the exploration of the optimum can be advanced at the same time by maximizing EI value. In this study, a total of 90 sample points are evaluated using the Reynolds averaged Navier-Stokes simulation(RANS) for the construction of the Kriging model. In order to obtain the information of the design space, two data mining techniques are applied to design result. One is functional Analysis of Variance(ANOVA) which can show quantitative information and the other is Self-Organizing Map(SOM) which can show qualitative information.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1551-1554
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• 2010

우량계 자료를 참 값이라고 가정할 때 레이더 자료에는 크게 두 가지 문제점이 나타난다. 평균의 차이로 인한 편의의 문제와 불확실성으로 인한 변동성의 문제가 그것이다. 두 가지 문제점으로 인해 발생하는 오차를 모두 고려할 수 있는 자료의 품질평가 방안으로 유철상과 윤정수(2009)는 통계학 분야의 분산분석과 유사한 방법론을 제시하였다. 그러나 이러한 방법론은 호우사상에 따라 가용한 레이더 강우와 우량계 강우 쌍의수가 다르기 때문에 서로 비교 평가할 수 없는 문제점을 가지고 있다. 이에 본 연구에서는 자료 쌍의 수에 영향을 받지 않는 레이더 강우의 품질기준(RRQC, Radar Rain rate Quality Criterion)을 제안하였다. 제안된 방법론에 따르면 우량계 강우와 레이더 강우가 완벽하게 일치하는 경우 100%의 품질이 되고 레이더 자료가 모두 0이면 0%가 된다. 위 기준은 충주댐 유역에서의 태풍 루사(2002년)와 대류성 강우(2003) 사상의 원자료, G/R 보정된 자료, CoKriging된 자료, G/R 보정 후 CoKriging된 자료에 적용하였다.

• Korean Journal of Remote Sensing
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• v.7 no.1
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• pp.45-67
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• 1991

An overview is given on stochastic techniques with which remotely sensed data may be used together with ground measurements for purposes of state estimation and prediction. They can explicitly account for spatiotemporal differences in measurement characteristics between ground measurements and remotely sensed data, and are suitable for highly variant space or space-time processes, such as atmosperic processes, which may be viewed as (containing) a random process. For state estimation of static ststems, optimal linear estimation is described. As alternatives, various co-kriging estimation techniques are also described, including simple, ordinary, universal, lognormal, disjunctive, indicator, and Bayesian extersion to simple and lognormal. For illustrative purposes, very simple examples of optimal linear estimation and simple co-kriging are given. For state estimation and prediction of dynamic system, distributed-parameter kalman filter is described. Issues concerning actual implemention are given, and with application potential are described.