Results 161 to 170 of about 6,631 (202)

Privacy-Preserving Kriging Interpolation on Distributed Data

2014
Kriging 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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Taylor Kriging Metamodeling for Stochastic Simulation Interpolation

International Journal of Operations Research and Information Systems, 2011
This 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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Compositional Kriging: A Spatial Interpolation Method for Compositional Data

Mathematical Geology, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Walvoort, D.J.J., de Gruijter, J.J.
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Spatial distribution of the groundwater quality using kriging and Co-kriging interpolations

Groundwater for Sustainable Development, 2020
Abstract 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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Smoothing and interpolation by kriging and with splines

Journal of the International Association for Mathematical Geology, 1984
Let 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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Kriging for Localized Spatial Interpolation in Sensor Networks

2008
The 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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Using Kriging to interpolate MRI data

Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2002
Volumetric 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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Object removal by Kriging Interpolation Technique

2015 International Conference on Cognitive Computing and Information Processing(CCIP), 2015
Object 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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Generalized Kriging Model for Interpolation and Regression

Transactions of the Korean Society of Mechanical Engineers A, 2005
Kriging 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 Interpolation in Simulation: A Survey [PDF]

Proceedings of the 2004 Winter Simulation Conference, 2004., 2005
van Beers, W.C.M., Kleijnen, J.P.C.
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