منابع مشابه
Part 4: Spatial Prediction and Kriging
where the covariance structure of U(s) is unknown. The prediction of U(s) at a new spatial site s0 is known as kriging (though the term has been mainly used for the construction of a spatial predictor using a model with known parameters). A generalization is to predict the joint value at several points, or an integral such as u(A) = ∫ A u(s) ds doe some set A (commonly of interest in areal data...
متن کاملSpatial Prediction of Soil Organic Matter Using a Hybrid Geostatistical Model of an Extreme Learning Machine and Ordinary Kriging
An accurate estimation of soil organic matter (SOM) content for spatial non-point prediction is an important driving force for the agricultural carbon cycle and sustainable productivity. This study proposed a hybrid geostatistical method of extreme learning machine-ordinary kriging (ELMOK), to predict the spatial variability of the SOM content. To assess the feasibility of ELMOK, a case study w...
متن کاملOn the reduction of the ordinary kriging smoothing effect
A simple but novel and applicable approach is proposed to solve the problem of smoothing effect of ordinary kriging estimate which is widely used in mining and earth sciences. It is based on transformation equation in which Z scores are derived from ordinary kriging estimates and then rescaled by the standard deviation of sample data and the sample mean is added to the result. It bears the grea...
متن کاملPredicting ordinary kriging errors caused by surface roughness and dissectivity
The magnitude of kriging errors varies in accordance with the surface properties. The purpose of this paper is to determine the association of ordinary kriging (OK) estimated errors with the local variability of surface roughness, and to analyse the suitability of probabilistic models for predicting the magnitude of OK errors from surface parameters. This task includes determining the terrain p...
متن کاملParallel ordinary kriging interpolation incorporating automatic variogram fitting
This work introduces a methodology for reducing the execution time of the kriging interpolationmethod without losing the quality of the model results, as occurs in simplified moving neighborhood solutions. The proposed solution distributes the computation applying parallel programming using MPI (Message Passing Interface) libraries in a HPC (High Performance Computing) environment. For the solu...
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ژورنال
عنوان ژورنال: Mathematical Geology
سال: 1989
ISSN: 0882-8121,1573-8868
DOI: 10.1007/bf00897332