• KIPS Transactions on Computer and Communication Systems
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• v.3 no.8
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• pp.251-260
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• 2014

3D point data is utilized in various industry domains for its high accuracy to the surface information of an object. It is substantially utilized in geography for terrain scanning and analysis. Generally, 3D point data need to be changed by Gridding which produces a regularly spaced array of z values from irregularly spaced xyz data. But it requires long processing time and high resource cost to interpolate grid coordination. Kriging interpolation in Gridding has attracted because Kriging interpolation has more accuracy than other methods. However it haven't been used frequently since a processing is complex and slow. In this paper, we presented a parallel Gridding algorithm which contains Kriging and an application of grid data structure to fit MapReduce paradigm to this algorithm. Experiment was conducted for 1.6 and 4.3 billions of points from Airborne LiDAR files using our proposed MapReduce structure and the results show that the total execution time is decreased more than three times to the convention sequential program on three heterogenous clusters.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.1630-1638
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• 2015

The finite element analysis has become an essential process to investigate the structural performance in many industry fields. In addition, the computer's performance is improving rapidly, but in large design problems, there is a limit to apply the optimal design techniques. For this, it is general to introduce a metamodel based optimization technique. The method to generate an approximate model can be classified into curve fitting and interpolation, and each representative one is response surface model and kriging interpolation method. This study proposes an ensemble model made of RSM and kriging to solve a structural design problem. The suggested method is applied to the designs of two bar and automobile outer tie rod.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.422-427
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• 2008

This study is to illustrate the usefulness of Kriging Dimension Reduction Method(KDRM), which is to construct probability distribution of response function in the presence of the physical uncertainty of input variables. DRM has recently received increased attention due to its sensitivity-free nature and efficiency that considerable accuracy is obtained with only a few number of analyses. However, the DRM has a number of drawbacks such as instability and inaccuracy for functions with increased nonlinearity. As a remedy, Kriging interpolation technique is incorporated which is known as more accurate for nonlinear functions. The KDRM is applied and compared with MCS methods in a compression coil spring design problem. The effectiveness and accuracy of this method is verified.

• Journal of computational fluids engineering
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• v.13 no.1
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• pp.41-48
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• 2008

The fluid-structure interaction analysis such as a static aeroelastic analysis requires the result of each analysis as an input to the other analysis. Usually the grids for the fluid analysis and the structural analysis are different, so the results should be transformed properly for each other. The Infinite Plate Spline(IPS) and the Thin Plate Spline(TPS) are used in interpolating the displacement and the pressure. In this study, such interpolation methods are compared with kriging which provides a precise response surface. The static aeroelastic analysis is performed for the supersonic flow field with shock waves and the pressure field is interpolated by the TPS and kriging. The TPS shows tendency to weaken the shock strength, whereas kriging preserves the shock strength.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.141-144
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• 2005

The fluid-structure interaction analysis such as a static aeroelastic analysis requires the result of each analysis as an input to other analysis. Usually the grids for the fluid analysis and the structural analysis are different, so the results should be transformed properly for each other. The Infinite Plate Spline(IPS) and the Thin Plate Spline(TPS) are used in interpolating the displacement and the pressure. In this study, such interpolation methods are compared with kriging which provides a precise response surface. The static aeroelastic analysis is performed for the supersonic flow field with shock waves and the pressure field is interpolated by the TPS and kriging. The TPS shows tendency to weaken the shock stength, whereas kriging preserves the shock strength.

• Journal of the Korean Geotechnical Society
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• v.38 no.10
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• pp.17-29
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• 2022

Recently, the interest in integrated underground geospatial information mapping (IUGIM) to ensure the safety of underground spaces and facilities has been increasing. Because IUGIM is used in the fields of underground space development and underground safety management, the up-to-dateness and accuracy of information are critical. In this study, IUGIM and field data were classified, and the accuracy of IUGIM was improved by spatial interpolation. A spatial interpolation technique was used to process borehole data in IUGIM, and a quantitative evaluation was performed with mean absolute error and root mean square error through the cross-validation of seven interpolation results according to the technique and model. From the cross-validation results, accuracy decreased in the order of nonuniform rational B-spline, Kriging, and inverse distance weighting. In the case of Kriging, the accuracy difference according to the variogram model was insignificant, and Kriging using the spherical variogram exhibited the best accuracy.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.43-51
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• 2012

Due to the increasing demand to utilize water fronts and water resource effectively, a multi-dimensional model that provides detailed hydraulic characteristics is required in order to improve the decision making process. An EFDC model is a kind of multi-dimension model, and it requires detailed 3D (3-dimensional) terrain in order to simulate the hydraulic characteristics of stream flow. In the case of 3D terrain creation, especially river reaches, measurement resolution and spatial interpolation methods affect the detailed 3D topography which uses input data for EFDC simulation. Such results make hydraulic characteristics to be varied. This study aims to examine EFDC simulation results depending on the 3D topographies derived by separate measurement resolution and spatial interpolation methods. The study area is at the confluence of the Nakdong and Kuemho Rivers and the event rain implemented was Typhoon Ewiniar in 2006. As a result, in the case of the area-elevation curve, the difference by means of the interpolation methods was significant when applying the same measurement resolution, except at 160m resolution. Furthermore, when the measurement resolution was 80m or above, the difference in a cross-section was occurred. Meanwhile, the water level changes between interpolation methods were insignificant by the measurement resolution except when the Kriging method was used for the 160m measurement data. Velocity changes emerged according to the interpolation methods when measurement resolution was 80m or above and the Kriging method resulted in a velocity that had a considerable gap in relation to the results from other methods at a measurement resolution of 160m.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.29-41
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• 2010

In this study, the prediction errors of various spatial interpolation methods used to model values at unmeasured locations was compared and the accuracy of these predictions was evaluated. The root mean square (RMS) was calculated by processing different parameters associated with spatial interpolation by using techniques such as inverse distance weighting, kriging, local polynomial interpolation and radial basis function to known elevation data of the east coastal area under the same condition. As a result, a circular model of simple kriging reached the smallest RMS value. Prediction map using the multiquadric method of a radial basis function was coincident with the spatial distribution obtained by constructing a triangulated irregular network of the study area through the raster mathematics. In addition, better interpolation results can be obtained by setting the optimal power value provided under the selected condition.

• Journal of Climate Change Research
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• v.5 no.4
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• pp.323-329
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• 2014

Since the terrain of Korea is complex, micro- as well as meso-climate variability is extreme by locations in Korea. In particular, air temperature of agricultural fields is influenced by topographic features of the surroundings making accurate interpolation of regional meteorological data from point-measured data. This study was carried out to compare spatial interpolation methods to estimate air temperature in agricultural fields surrounded by rugged terrains in South Korea. Four spatial interpolation methods including Inverse Distance Weighting (IDW), Spline, Ordinary Kriging (with the temperature lapse rate) and Cokriging were tested to estimate monthly air temperature of unobserved stations. Monthly measured data sets (minimum and maximum air temperature) from 588 automatic weather system(AWS) locations in South Korea were used to generate the gridded air temperature surface. As the result, temperature lapse rate improved accuracy of all of interpolation methods, especially, spline showed the lowest RMSE of spatial interpolation methods in both maximum and minimum air temperature estimation.