• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.317-324
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• 2003

Kriging interpolation is one of the gennerally used interpolation techniques in Geostatics field. This research refers to the contents about important experimental variogram and the study of theoretical variogram and formulation of Kriging interpolation. Kriging interpolation is applied as interpolation for stress smoothing in finite element method. Posteriori error estimation which makes use of stress smoothing from the FEM is very important part, we try to make practical application of surface regeneration ability from Kriging interpolation. This research is necessary preceding one in order to materialize adaptive FTM through posteriori error estimation. For instance, find the estimate value and estimate the propriety through various theoretical variogram models of the reference analyzed from tensional L-shape domain. It also provides possibility of the Kriging interpolation through comparing to existing Least square method as well.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.135-140
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• 2007

In this paper, an Improved Dimension Reduction(IDR) method is proposed for uncertainty quantification that employes Kriging interpolation technic. It has been acknowledged that the DR method is accurate and efficient for assessing statistical moments and reliability due to the sensitivity free feature. However, the DR method has a number of drawbacks such as instability and inaccuracy for problems with increased nonlineality. In this paper, improved DR is implanted by three steps. First, the Kriging interpolation method is used to accurately approximate the responses. Second, 2N+1 and 4N+1 ADOEs are proposed to maintain high accuracy of the method for UQ analysis. Third, numerical integration scheme is used with accurate but free response values at any set of integration points of the surrogated model.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.134-147
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• 2015

This paper presents the applications of Kriging spatial interpolation methods for meteorologic variables, including temperature and relative humidity, in regions of Vietnam. Three types of interpolation methods are used, which are as follows: Ordinary Kriging, Universal Kriging, and Universal Kriging plus Digital Elevation model correction. The input meteorologic data was collected from 98 ground weather stations throughout Vietnam and the outputs were interpolated temperature and relative humidity gridded fields, along with their error maps. The experimental results showed that Universal Kriging plus the digital elevation model correction method outperformed the two other methods when applied to temperature. The interpolation effectiveness of Ordinary Kriging and Universal Kriging were almost the same when applied to both temperature and relative humidity.

• 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.

• 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.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1479-1481
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• 2003

The aim of this paper was mainly to interpret the real information-missing patch of image by using the kriging interpolation technology of spatial statistics. The TM Image of the Jingouling Forest Farm of Wangqing Forestry Bureau of Northeast China on 1 July 1997 was used as the tested material in this paper. Based on the classification for the TM image, the information pixel-missing patch of image was interpolated by the kriging interpolation technology of spatial statistics theory under the image treatment software-ERDAS and the geographic information system software-Arc/Info. The interpolation results were already passed precise examination. This paper would provide a method and means for interpreting the information-missing patch of image.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.5
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• pp.1-7
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• 2011

The objective of this study is to decide a spatial interpolation method on temperature data for the suitability analysis of garlic cultivation. In Korea, garlic is the second most cultivated condiment vegetable after red pepper. Nowadays warm-temperate garlic faces potential shift of its arable area according to warmer temperature in the Korean Peninsula, and the change can be drawn with the precise temperature map derived from interpolation on point-measured data. To find the preferable interpolation method in cases of germination and vegetative period of the garlic, different approaches were tested as follows: Inverse Distance Weighted (IDW), Spline, Ordinary Kriging (OK), and Universal Kriging (UK). As a result, IDW and UK show the lowest root mean square errors as for the germination and vegetative seasons, respectively. However, statistically significant difference was not revealed among the applied methods regarding the germinating period. Eventually this will contribute to mapping the suitable lands for the cultivation of warm-temperate garlic reasonably.

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.443-452
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• 2006

Today, satellite remote sensing (RS) and geographic information systems (GIS) plays an important role as an advanced science and technology. This study was developed a Line Density Algorithm which was clarify and describe the thermal front by using NOAA SST (sea surface temperature) and GIS spatial analysis for systemic and effective management of fish raising industry and sea environmental pollution by land reclamation program. Before this, a study about a interpolation method was carry out which was very important for estimate the hidden value between a special point. For this study Inverse Distance Weighted interpolation, Spline interpolation, Kriging interpolation methods were choose and SST data from 2001 to 2004 in spring (March, April, May) were analyzed. According to the study Kriging interpolation method was the very adaptive method from a practical point of view and excellent in description and precision then others. Finally, the result of this study will be use for develope the Line Density Index Algorism.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.4
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• pp.684-689
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• 2006

Rainfall is the most basic input data to analyze the hydrologic system. When we measure the rainfall data, the rainfall data can be missing due to various reasons. Therefore, various interpolation methods are available for compensating the missing data. However, the interpolation methods were used without considering their applicability and accuracy. This study compares the interpolation methods such as the arithmetic mean method, normal ratio method, modified normal ratio method, inverse distance method, linear programming, Kriging method to estimate the existing rainfall correction method.

• Water Engineering Research
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• v.5 no.3
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• pp.123-131
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• 2004

This paper describes the use of spatial interpolation for estimating seasonal crop potential evapotranspiration (PET) and irrigation water requirement in unmeasured evaporation gage stations within Edwards Aquifer, Texas using GIS. The Edwards Aquifer area has insufficient data with short observed records and rare gage stations, then, the investigation of data for determining of irrigation water requirement is difficult. This research shows that spatial interpolation techniques can be used for creating more accurate PET data in unmeasured region, because PET data are important parameter to estimate irrigation water requirement. Recently, many researchers are investigating intensively these techniques based upon mathematical and statistical theories. Especially, three techniques have well been used: Inverse Distance Weighting (IDW), spline, and kriging (simple, ordinary and universal). In conclusion, the result of this study (Table 1) shows the kriging interpolation technique is found to be the best method for prediction of unmeasured PET in Edwards aquifer, Texas.