نتایج جستجو برای: lognormal kriging

تعداد نتایج: 7298  

Journal: :The Science of the total environment 2006
N Saby D Arrouays L Boulonne C Jolivet A Pochot

This paper presents a survey on soil Pb contamination around Paris (France) using the French soil monitoring network. The first aim of this study is to estimate the total amount of anthropogenic Pb inputs in soils and to distinguish Pb due to diffuse pollution from geochemical background Pb. Secondly, this study tries to find the main controlling factors of the spatial distribution of anthropog...

Journal: :Japanese journal of applied statistics 1988

Journal: :J. Comput. Physics 2015
Pierric Kersaudy Bruno Sudret Nadège Varsier Odile Picon Joe Wiart

In numerical dosimetry, the recent advances in high performance computing led to a strong reduction of the required computational time to assess the specific absorption rate (SAR) characterizing the human exposure to electromagnetic waves. However, this procedure remains time-consuming and a single simulation can request several hours. As a consequence, the influence of uncertain input paramete...

2012
John H. Graham Daniel T. Robb Amy R. Poe

BACKGROUND Distributed robustness is thought to influence the buffering of random phenotypic variation through the scale-free topology of gene regulatory, metabolic, and protein-protein interaction networks. If this hypothesis is true, then the phenotypic response to the perturbation of particular nodes in such a network should be proportional to the number of links those nodes make with neighb...

Journal: :CoRR 2013
Firas Ajil Jassim Fawzi Hasan Altaany

Image interpolation has been used spaciously by customary interpolation techniques. Recently, Kriging technique has been widely implemented in simulation area and geostatistics for prediction. In this article, Kriging technique was used instead of the classical interpolation methods to predict the unknown points in the digital image array. The efficiency of the proposed technique was proven usi...

2014
C. K. NG

The coefficient of variation is often used as a measure of precision in medical and biological sciences. When it is known a priori that several independent normal populations have equal coefficient of variations, procedures for constructing confidence intervals for the common coefficient of variation based on the concept of generalized variables had been discussed by other researchers. This pap...

2008
C. Fischione M. D’Angelo

In this report we propose an approximation of the outage probability of the Signal to Interference plus Noise Ratio for a CDMA system in a Rayleigh-lognormal fading environment. Specifically, the SINR is approximated as an overall lognormal random variable. The approximation moves from the one proposed in [1] for the product of Rayleigh-lognormal random variables, and from the method presented ...

Journal: :CoRR 2017
Bas van Stein Hao Wang Wojtek Kowalczyk Michael T. M. Emmerich Thomas Bäck

Kriging or Gaussian Process Regression is applied in many fields as a non-linear regression model as well as a surrogate model in the field of evolutionary computation. However, the computational and space complexity of Kriging, that is cubic and quadratic in the number of data points respectively, becomes a major bottleneck with more and more data available nowadays. In this paper, we propose ...

Journal: :CoRR 2013
Firas Ajil Jassim

Image denoising is a critical issue in the field of digital image processing. This paper proposes a novel Salt & Pepper noise suppression by developing a Kriging Interpolation Filter (KIF) for image denoising. Gray-level images degraded with Salt & Pepper noise have been considered. A sequential search for noise detection was made using kk window size to determine nonnoisy pixels only. The non...

2017
François Bachoc Nicolas Durrande Didier Rullière Clément Chevalier

Kriging is a widely employed technique, in particular for computer experiments, in machine learning or in geostatistics. An important challenge for Kriging is the computational burden when the data set is large. We focus on a class of methods aiming at decreasing this computational cost, consisting in aggregating Kriging predictors based on smaller data subsets. We prove that aggregations based...

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