Results 191 to 200 of about 37,687 (235)
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Taylor Kriging Metamodeling for Stochastic Simulation Interpolation
International Journal of Operations Research and Information Systems, 2011This paper applies a novel Kriging model to the interpolation of stochastic simulation with high computational expense. The novel Kriging model is developed by using Taylor expansion to construct a drift function for Kriging, thus named Taylor Kriging. The interpolation capability of Taylor Kriging for stochastic simulation is empirically compared with
Heping Liu, Yanli Chen
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Privacy-Preserving Kriging Interpolation on Distributed Data
2014Kriging is one of the most preferred geostatistical methods in many engineering fields. Basically, it creates a model using statistical properties of all measured points in the region, where a prediction value is sought. The accuracy of the kriging model depends on the total number of measured points. Acquiring sufficient number of measurement requires
Bulent Tugrul, Huseyin Polat 0001
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Kriging interpolation on high-performance computers
1998We discuss Kriging Interpolation on high-performance computers as a method for spatial data interpolation. We analyse algorithms for implementing Kriging on high-performance and distributed architectures. In addition to a number of test problems, we focus on an application of comparing rainfall measurements with satellite imagery.
K. E. Kerry, Kenneth A. Hawick
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Smoothing and interpolation by kriging and with splines
Journal of the International Association for Mathematical Geology, 1984Let scalar measurements at distinct points x1, ⋯, xn be y1, ⋯, yn.We may look for a smooth function f(x)that goes through or near the points (xi, yi).Kriging assumes f(x)is a random function with known (possibly estimable) covariance function (in the simplest case).
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Spatial distribution of the groundwater quality using kriging and Co-kriging interpolations
Groundwater for Sustainable Development, 2020Abstract The present work is aimed for investigation the groundwater quality for drinking purposes in El Mila plain, Algeria. This is carried out through an integrated approach of groundwater quality index (GWQI) and geostatistical method for mapping this index based on 35 wells and then hydrochemical parameters.
Lazhar Belkhiri, Ammar Tiri, Lotfi Mouni
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Using Kriging to interpolate MRI data
Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2002Volumetric medical MRI data is statistically analyzed to justify representing the data as regionalized variables (REVs) that may be optimal interpolated using kriging in conjunction with a volumetric structural analysis of the modality space (MS) data. With kriging, the interpolation estimation error may be determined and subsequently projected in the ...
S.M. Matechik, M.R. Stytz
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Compositional Kriging: A Spatial Interpolation Method for Compositional Data
Mathematical Geology, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Walvoort, D.J.J., de Gruijter, J.J.
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Generalized Kriging Model for Interpolation and Regression
Transactions of the Korean Society of Mechanical Engineers A, 2005Kriging model is widely used as design analysis and computer experiment (DACE) model in the field of engineering design to accomplish computationally feasible design optimization. In general, kriging model has been applied to many engineering applications as an interpolation model because it is usually constructed from deterministic simulation ...
Jae Jun Jung, Tae Hee Lee
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Kriging for Localized Spatial Interpolation in Sensor Networks
2008The presence of coverage holes can adversely affect the accurate representation of natural phenomena being monitored by a Wireless Sensor Network (WSN). Current WSN research aims at solving the coverage holes problem by deploying new nodes to maximize the coverage. In this work, we take a fundamentally different approach and argue that it is not always
Muhammad Umer, Lars Kulik, Egemen Tanin
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Object removal by Kriging Interpolation Technique
2015 International Conference on Cognitive Computing and Information Processing(CCIP), 2015Object removal in an image, is very useful in image processing field. Most often there comes a need to remove some scratches, small objects, unwanted text or logos from images. It can be done manually with a lot of effort and time. So, automatic version of this method is required through which it can be done easily and in lesser time.
Lakshmi Bhanu Bangaru, Vimal Gupta
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