• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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• pp.288-295
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• 2003

The relationship between the reflection number obtained from seismic reflective survey and the rock strength value obtained from TBM excavation is examined, and the procedure of the conversion from the reflection number to the rock strength value is proposed. Subsequently, geostatistical method is employed to evaluate the rock properties ahead of the tunnel face and around the tunnel with good precision, using both the seismic reflective survey data and the TBM driving data for the purpose of the tunnel driving and enlargement. The applicability of this evaluation method is examined at the actual tunnel site.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2009년도 특별 심포지엄
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• pp.101-118
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• 2009

In order to invest in overseas mineral projects, it is necessary to have a ability of technical and financial evaluation. Reserve estimation is the most important for mineral appraisal. Geostatistical evaluation of tonnage and grade promises more accurate reserve estimation than traditional methods such as polygon, inverse distance method and so on even if it has some uncertainty. Selection of a mining method and a mineral processing is also important because capex and opcosts of a mineral project is due to the selection. Mineral project is usually evaluated financially using NPV and IRR which are calculated through DCF(Discount Cash Flow). Uncertainty of a mineral project is analyzed statistically using sensitivity analysis and montecarlo simulation.

• 한국농공학회논문집
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• 제49권1호
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• pp.3-13
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• 2007

In this study, spatial characteristics of rainfall in Imha basin were investigated by cross-correlation analysis among rainfall gaging stations and rainfall-runoff analysis used in HEC-HMS model for analysis of influence on observed rainfall. The Kriging technique was applied to rain(all analysis in Imha basin to reflect spatial characteristics of regional rainfall. Their results are compared to rainfall-runoff data with spatially distributed rainfall data as well as the classical thiessen method. The results by kriging technique approached by geostatistical method could reflect spatial characteristics of regional rainfall properly in Imha basin.

• Nuclear Engineering and Technology
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• 제30권6호
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• pp.485-495
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• 1998

Migration characteristics of tracers in a rock fracture in a case of line-source and line-collection was studied. The fracture plane was discretized into a square mesh to which variable apertures were assigned. The spatially varying apertures of a fracture were generated using a geostatistical method, based on a given aperture probability density distribution and a specified spatial correlation length. The flow potential and pressure at each node were computed. Calculations showed that fluid flow occurs predominantly through a few preferred paths. Hence, the large range of apertures in the fracture gives rise to flow channeling. The solute transport was calculated using a particle tracking method. The migration plumes of tracer between injection line and withdrawal line are displayed in contour plots. The elution curves are shown to be controlled by the aperture density distribution and to be insensitive to statistical realization and spatial correlation length.

• 한국지리정보학회지
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• 제13권4호
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• pp.138-147
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• 2010

부정확한 교통량 예측은 잘못된 교통계획 및 설계를 초래할 수 있으므로, 교통량 데이터를 이용한 교통량 예측은 교통계획 및 운영과 같은 공간의사결정과정에서 매우 중요하다. 교통량 예측의 정확도 향상을 위해 최근 공간통계분석방법인 크리깅 방법론을 이용한 연구들이 발표되고 있으며, 연구결과 기존의 전통적인 방법에 비하여 예측력이 높게 나타났다. 이에 본 연구는 먼저 미국 미주리 주의 세인트루이스를 대상으로 크리깅 분석방법론을 이용하여 교통량 데이터를 예측한 후 실제 측정값과 비교하여 그 정확도를 검증하였다. 이후 크리깅 방법론의 예측 값을 더욱 향상 시키기 위한 새로운 방안을 제시하였다. 그 방안으로 첫째, 베리오그램 인자 결정시 나타난 교통량 데이터의 특징인 이방성을 적용하였으며, 둘째, 교통량 데이터의 공간적 상관관계가 높은 주간고속도로를 이차변수로 설정하여 공동크리깅 분석을 실시하였다. 분석결과 일반 크리깅 방법보다 이방성을 적용한 분석에서 더욱 높은 정확도 나타났으며, 이방성의 적용 하에 실시한 공동크리깅의 결과에서 가장 좋은 예측 값이 나타났다.

• 자원환경지질
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• 제30권5호
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• pp.493-498
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• 1997

The purpose of this study is to develop geostatistical model for evaluating the abundance of deep-sea manganese nodule. The abundance data used in this study were obtained from the KODOS (Korea Deep Ocean Study) area. The variation of nodule abundance was very high within short distance, while sampling methods was very limited. As the distribution of nodule abundance showed non-gaussian, indicator simulation method was used instead of conditional simulation method and/or ordinary kriging. The abundance data were encoded into a series of indicators with 6 cutoff values. They were used to estimate the conditional probability distribution function (cpdf) of the nodule abundance at any unsampled location. The standardized indicator variogram models were obtained according to variogram analysis. This SIS method had the advantage over other traditional techniques such as the turning bands method and ordinary kriging. The estimating values by indicator conditional simulation near high abundance area were more detailed than by ordinary kriging and indicator kriging. They also showed better spatial characteristics of distribution of nodule abundance.

• 한국측량학회지
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• 제36권2호
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• pp.95-104
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• 2018

이 연구는 공간통계 기법을 이용하여 공시지가에 대한 만족도를 시계열적으로 분석하기 위한 방법을 제시하는데 목적이 있다. 현재 GIS를 이용한 공시지가의 공간적 분포특성을 분석하거나, 공시지가 제도의 개선 방안을 정성적으로 제시하는데 머무르고 있다. 공시지가의 공시가격, 의견가격을 기준으로 이의신청 제기 강도를 그룹화 하여 공시지가에 대한 만족도 GIS DB를 구축하고, 공간밀도분석과 공간 자기상관분석을 통해서 만족도의 시계열적 변화를 비교 분석하였다. 연구 결과 공시가격과 의견가격과의 차이는 개별토지에 따라 다르나 대부분 평균 3배 이하의 상향 또는 하향을 요구하고 있는 것을 알 수 있었으며, 이를 통해 민원인들의 의견가격의 요구를 통계적으로 분석함으로써 민원인의 공시지가에 대한 만족도를 정량적으로 나타낼 수 있음을 알 수 있었다. 공시지가의 만족도를 GIS를 이용하여 분석함으로써 공시지가만이 아닌 의견가격과의 차이를 이용하여 공시지가의 만족도를 분석할 수 있음을 알 수 있었다. 공간 자기상관 분석 및 핫스팟 분석 등의 시계열적 공간통계분석 방법을 통해 공시지가 만족도의 시공간적 변화를 분석할 수 있음을 알 수 있었다. 즉, 연도별 자료를 활용한 시공간 분석을 통하여 지역적으로 양 또는 음의 유의적 관계를 규명할 수 있었다.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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• pp.340-343
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• 2003

This study presents a practical procedure for the Bayesian inversion of geophysical data by Markov chain Monte Carlo (MCMC) sampling and geostatistics. We have applied geostatistical techniques for the acquisition of prior model information, and then the MCMC method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter. This approach provides an effective way to treat Bayesian inversion of geophysical data and reduce the non-uniqueness by incorporating various prior information.

• Journal of the Korean Statistical Society
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• 제36권1호
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• pp.57-76
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• 2007

Kriging is a nonparametric regression method used in geostatistics for estimating curves and surfaces for spatial data. It may come as a surprise that the Kriging estimator, normally derived as the best linear unbiased estimator, is also the solution of a particular variational problem. Thus, Kriging estimators can also be interpreted as generalized smoothing splines where the roughness penalty is determined by the covariance function of a spatial process. We build off the early work by Silverman (1982, 1984) and the analysis by Cox (1983, 1984), Messer (1991), Messer and Goldstein (1993) and others and develop an equivalent kernel interpretation of geostatistical estimators. Given this connection we show how a given covariance function influences the bias and variance of the Kriging estimate as well as the mean squared prediction error. Some specific asymptotic results are given in one dimension for Matern covariances that have as their limit cubic smoothing splines.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2000년도 추계학술대회
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• pp.262-265
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• 2000

In order to estimate spatial physicochemical properties of the spring waters in the study area, spring waters at 57 sites were investigated for measuring ten items (temperature, pH, Eh, EC, TDS, DO, salinity, alkalinity, discharge rate, and surface elevation), To compare each component with one another, regression analysis was carried out. Kriging was used to estimate the spatial characteristics and continuity of data in the study area. To solve kriging equation, the semivariogram was calculated using geostatistical software GS$^{+}$(version 3.1). As a result of semivariogram analysis, the data of nine components but surface elevation could be assumed as stationary random function, and ordinary kriging method was used for making contour maps.s.