• 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.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.423-432
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• 2003

The data observed at different positions are called the estimate of interested variable at new observation point on the Kriging utilize the space estimate technique, in which case there is correlation spatially. In this paper we provide the estimate for Variogram and Kriging methods as a field of kriging theory and dealt with actually measured data. And at the same time we forecast the amount of ozone that was not measured at this point by Kriging method and compared Ordinary Kriging method with Inverse Distance Kriging method.

• Journal of Wetlands Research
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• v.15 no.1
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• pp.115-125
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• 2013

This study established a methodology for the application of downscaling technique in a mountainous area having large spatial variations of rainfall and tried to estimate the change of rainfall characteristics in the future under climate change using the established method. The Namhan river basin, which is in the mountainous area of the Korean peninsula, has been chosen as the study area. Artificial Neural Network - Simple Kriging with varying local means (ANN-SKlm) has been built by combining artificial neural network, which is one of the general downscaling techniques, and SKlm technique, which can reflect the geomorphologic characteristics like elevation of the study area. The evaluation of SKlm technique was done by using the monthly rainfalls at six weather stations which KMA(Korea Meteorological Administration) is managing in the basin. The ANN-SKlm technique was compared with the Thiessen technique and ordinary kriging(OK) technique. According to the evaluation result of each technique the SKlm technique showed the best result.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.677-687
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• 2006

Kriging interpolation is one of the generally used interpolation techniques in Geostatistics field. This technique includes the experimental and theoretical variograms and the formulation of kriging interpolation. In contrast to the conventional least square method for stress recovery, kriging interpolation is based on the weighted least square method to obtain the estimated exact solution from the stress data at the Gauss points. The weight factor is determined by variogram modeling for interpolation of stress data apart from the conventional interpolation methods that use an equal weight factor. In addition to this, the p-level is increased non-uniformly or selectively through a posteriori error estimation based on SPR (superconvergent patch recovery) technique, proposed by Zienkiewicz and Zhu, by auto mesh p-refinement. The cut-out plate problem under tension has been tested to validate this approach. It also provides validity of kriging interpolation through comparing to existing least square method.

• Journal of computational fluids engineering
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• v.17 no.4
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• pp.32-40
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• 2012

Efficient Global Optimization (EGO) method is a global optimization technique which can select the next sample point automatically by infill sampling criteria (ISC) and search for the global minimum with less samples than what the conventional global optimization method needs. ISC function consists of the predictor and mean square error (MSE) provided from the kriging model which is a stochastic metamodel. Also the constrained EGO method can minimize the objective function dealing with the constraints under EGO concept. In this study the constrained EGO method applied to the RAE2822 airfoil shape design formulated with the constraint. But the noisy CFD data caused the kriging model to fail to depict the true function. The distorted kriging model would make the EGO deviate from the correct search. This distortion of kriging model can be handled with the interpolation(p=free) kriging model. With the interpolation(p=free) kriging model, however, the search of EGO solution was stalled in the narrow feasible region without the chance to update the objective and constraint functions. Then the accuracy of EGO solution was not good enough. So the three-step search method was proposed to obtain the accurate global minimum as well as prevent from the distortion of kriging model for the noisy constrained CFD problem.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.4
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• pp.149-154
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• 2008

The concept of robust design was introduced by Dr. G. Taguchi in the late 1940s, and his technique has become commonly known as the Taguchi method or the robust design. In this research, a robust design procedure for microgyroscope is suggested based on the kriging and optimization approaches. The kriging interpolation method is introduced to obtain the surrogate approximation model of true function. Robustness is calculated by the kriging model to reduce real function calculations. For this, objective function is represented by the probability of success, thus facilitating robust optimization. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.145-153
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• 2015

This study aims to accurately estimate population distribution more specifically than administrative unites using a RK (Regression-Kriging) model. The RK model is the areal interpolation technique that involves linear regression and the Kriging model. In order to estimate a population’s distribution using a sample region, four different models were used, namely; a regression model, RK model, OK (Ordinary Kriging) model and CK (Co-Kriging) model. The results were then compared with each other. Evaluation of the accuracy and validity of evaluation analysis results were the basis RMSE (Root Mean Square Error), MAE (Mean Absolute Error), G statistic and correlation coefficient (ρ). In the sample regions, every statistic value of the RK model showed better results than other models. The results of this comparative study will be useful to estimate a population distribution of the metropolitan areas with high population density

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.78-82
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• 2003

In this paper, simulated annealing technique was used to estimate the rock joint characteristics, RMR(rock mass rating) values, to overcome the defects of ordinary kriging. Ordinary kriging reduced the variance of data, so lost the characteristics of distribution. Simulated annealing technique could reflect the distribution feature and the spatial correlation of the original data. Through the comparisons between three times simulations, the uncertainty of the simulation could be quantified, and sufficient results were obtained.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.541-547
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• 2010

The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean$_0$ validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean$_0$ validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.538-550
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• 2008

Radon is an invisible, odorless, and radioactive gas. It is formed by the disintegration of radium, which is a decay product of uranium. Some amounts of radon gas and its products are present ubiquitously in the soil, water, and air. Particularly high radon levels occur in regions of high uranium content. Although radon is permeable into indoor environment not only through geological features (bed rock and permeability) but also through the construction materials and underground water, the radiation from the geological features is generally main exposure factor. So there can be a problem in a certain space such as the underground and/or relatively poor ventilation condition. In this study, a GIS technique was used in order to investigate spatial distribution of radon measured from sub- way stations of 1 thru 8 in Seoul, Korea in 1991, 1998, 2001, and 2006. Spatial analysis was applied to reproduce the radon distribution. We utilized spatial analysis techniques such as inverse distance weighted averaging (IDW) and kriging techniques which are widely used to relate between different spatial points. To validate the results from the analyses, the jackknife technique for an uncertainty test was performed. When the number of measuring sites was less than 100 and also when the number of omitted sites increased, the kriging technique was better than IDW. On the other hand, when the number of sites was over 100, IDW technique was better than kriging technique. Thus the selection of analytical tool was affected sensitives by the analysis based on the number of measuring sites.