• 호남수학학술지
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• 제26권1호
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• pp.87-103
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• 2004

A practical estimation method for groundwater contaminant concentration is introduced. Using geostatistical techniques and symmetry, experimental variograms show significant improved correlation compared with those from conventional techniques. Numrical experiments are performed using a field data set.

• 한국지하수토양환경학회지:지하수토양환경
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• 제20권3호
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• pp.51-64
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• 2015

In the present study, we develop two history matching techniques based on Markov chain Monte Carlo method where radial basis function and Gaussian distribution generated by unconditional geostatistical simulation are employed as the random walk transition kernels. The Bayesian inverse methods for aquifer characterization as the developed models can be effectively applied to the condition even when the targeted information such as hydraulic conductivity is absent and there are transient hydraulic head records due to imposed stress at observation wells. The model which uses unconditional simulation as random walk transition kernel has advantage in that spatial statistics can be directly associated with the predictions. The model using radial basis function network shares the same advantages as the model with unconditional simulation, yet the radial basis function network based the model does not require external geostatistical techniques. Also, by employing radial basis function as transition kernel, multi-scale nested structures can be rigorously addressed. In the validations of the developed models, the overall predictabilities of both models are sound by showing high correlation coefficient between the reference and the predicted. In terms of the model performance, the model with radial basis function network has higher error reduction rate and computational efficiency than with unconditional geostatistical simulation.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제5권
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• pp.493-502
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• 1997

An estimation method for groundwater level elevations is introduced. Using geostatistical techniques and anisotropies, experimental variograms show significant improved correlations compared with those from conventional techniques.

• 한국지구과학회지
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• 제23권1호
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• pp.15-29
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• 2002

Bayesian inversion for gravity and resistivity data was performed to investigate the cavity structure appearing as a lava tunnel in Cheju Island, Korea. Dipole-dipole DC resistivity data were proposed for a prior information of gravity data and we applied the geostatistical techniques such as kriging and simulation algorithms to provide a prior model information and covariance matrix in data domain. The inverted resistivity section gave the indicator variogram modeling for each threshold and it provided spatial uncertainty to give a prior PDF by sequential indicator simulations. We also presented a more objective way to make data covariance matrix that reflects the state of the achieved field data by geostatistical technique, cross-validation. Then Gaussian approximation was adopted for the inference of characteristics of the marginal distributions of model parameters and Broyden update for simple calculation of sensitivity matrix and SVD was applied. Generally cavity investigation by geophysical exploration is difficult and success is hard to be achieved. However, this exotic multiple interpretations showed remarkable improvement and stability for interpretation when compared to data-fit alone results, and suggested the possibility of diverse application for Bayesian inversion in geophysical inverse problem.

• Environmental Analysis Health and Toxicology
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• 제31권
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• pp.6.1-6.10
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• 2016

Objectives This study examined the spatial distribution and the extent of soil contamination by heavy metals resulting from primitive, unconventional informal electronic waste recycling in the Agbogbloshie e-waste processing site (AEPS) in Ghana. Methods A total of 132 samples were collected at 100 m intervals, with a handheld global position system used in taking the location data of the soil sample points. Observing all procedural and quality assurance measures, the samples were analyzed for barium (Ba), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn), using X-ray fluorescence. Using environmental risk indices of contamination factor and degree of contamination ($C_{deg}$), we analyzed the individual contribution of each heavy metal contamination and the overall $C_{deg}$. We further used geostatistical techniques of spatial autocorrelation and variability to examine spatial distribution and extent of heavy metal contamination. Results Results from soil analysis showed that heavy metal concentrations were significantly higher than the Canadian Environmental Protection Agency and Dutch environmental standards. In an increasing order, Pb>Cd>Hg>Cu>Zn>Cr>Co>Ba>Ni contributed significantly to the overall $C_{deg}$. Contamination was highest in the main working areas of burning and dismantling sites, indicating the influence of recycling activities. Geostatistical analysis also revealed that heavy metal contamination spreads beyond the main working areas to residential, recreational, farming, and commercial areas. Conclusions Our results show that the studied heavy metals are ubiquitous within AEPS and the significantly high concentration of these metals reflect the contamination factor and $C_{deg}$, indicating soil contamination in AEPS with the nine heavy metals studied.

• 대한수학회지
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• 제34권4호
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• pp.927-947
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• 1997

A practical estimation method for groundwater level elevations is introduced. Using geostatistical techniques with drift, averaging process and ratio, experimental variograms show significant improved coorelation compared with those from conventional techniques. The estimation method is applied to a field experimental data set.

• 지구물리와물리탐사
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• 제15권4호
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• pp.177-189
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• 2012

복합 물리탐사(전기비저항, MT)와 지질(시추 자료 및 코어 물성)정보에 대해 지구통계학적 복합해석 기법을 적용하여 3차원 광체 모델링 평가를 수행하였다. 우선, 복합 물리탐사를 통해 시추공 및 그 외의 전체적인 지역에 대한 비저항대 분포를 파악할 수 있었으며, 코어 물성 시험을 통해 연구지역의 자철석(광체)이 코어 내부의 밀도가 높은 전도성 성분(Fe)에 의해 밀도의 증가에 따라 비저항이 감소하는 상관관계를 나타냄을 파악하였다. 3차원 광체 모델링을 수행하기 위해 사용된 자료는 전기비저항 탐사, MT 탐사, 물성 자료와 시추 자료 등이며, 전체 획득 자료 및 시추 자료에서 추출한 광체의 품위 자료를 이용하였다. 본 연구에서는 자료의 복합 해석을 위해 지구통계학적 기법 중에서, 부족한 실제 측정 자료의 평균 및 분산을 잘 재생시키는 실현 값을 통해 지역적으로 변화하는 불균질성을 잘 묘사하는 순차 가우시안 시뮬레이션(sequential Gaussian simulation)을 사용하였다. 획득된 전체 자료와 품위 자료만을 이용하여 도출한 시뮬레이션 결과, 광체가 기존에 연구되어 존재하는 잔광체의 일정 부분에서 유사한 분포를 나타냈으며, 추가적으로 하부 깊은 심도에 대해 광체의 분포 양상을 추정할 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.

• KEPCO Journal on Electric Power and Energy
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• 제5권3호
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• pp.223-228
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• 2019

In order to integrate large amounts of variable generation resources such as wind and solar reliably into power grids, accurate renewable energy forecasting is necessary. Since renewable energy generation output is heavily influenced by environmental variables, accurate forecasting of power generation requires meteorological data at the point where the plant is located. Therefore, a spatial approach is required to predict the meteorological variables at the interesting points. In this paper, we propose the meteorological variable prediction model for enhancing renewable generation output forecasting model. The proposed model is implemented by three geostatistical techniques: Ordinary kriging, Universal kriging and Co-kriging.

• 한국지구과학회지
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• 제26권5호
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• pp.429-435
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• 2005

물리탐사와 시추자료에 대해 지구통계학적 복합해석 기술을 적용하여 3차원의 암반등급 해석을 수행하였다. 자료 복합 해석을 위한 다양한 지구통계학적 기술 중에서, 본 연구에서는 물리탐사 자료의 값을 추정하고자 하는 지점의 암반등급의 평균치로 치환하는 국소 변이 평균에 의한 단순 크리깅 기술(Simple Kriging with local varying means)을 사용하였다. 암석의 전기비저항 값은 RMR(Rock Mass Rating)값과 양의 상관관계를 갖는 것으로 알려져 있으나 상관 관계 만에 의한 대응방식은 그 양상이 매우 복잡하고 공간적으로 연관되어 있는 경우가 많아 단순히 적용하기 어려운 경우가 많다. 본 연구에서는 전기비저항과 RMR의 일반적 선형 상관관계 외에 지시자 변환(indicator transform)에 의한 비선형 상관관계를 유도하는 방식을 제안하였다. 또한 본 연구에서는 선형 및 비선형 상관관계에 의해 대응된 비저항 값이 실제 RMR과 비교할 때 나타나는 잔차(residual)에 대해 3차원 지구통계학적 분석을 적용하여 이 결과를 상관관계 결과에 추가함으로써 공간적 특성을 반영하는 RMR 평가를 수행할 수 있었다. 사용된 물리탐사 자료는 전기비저항 및 MT(Magnetotelluric) 탐사 자료이며, 총 10공의 시추자료를 통해 획득한 암반등급 값을 이용하였다. 이와 같은 해석은 조사 대상에 대한 광역적 지질조건을 보다 현실적으로 반영하는 암반등급 분포를 만들어내는 것으로 보인다.