نتایج جستجو برای: Ordinary kriging

تعداد نتایج: 53528  

2007
V. Roshan Joseph Ying Hung Agus Sudjianto

Kriging is a useful method for developing metamodels for product design optimization. The most popular kriging method, known as ordinary kriging, uses a constant mean in the model. In this article, a modified kriging method is proposed, which has an unknown mean model. Therefore it is called blind kriging. The unknown mean model is identified from experimental data using a Bayesian variable sel...

Journal: :Trilogi 2022

Geostatistika merupakan ilmu yang berfokus pada data spasial. Dalam geostatistika terdapat metode pendugaan untuk menangani variabel mempunyai nilai bervariasi dengan berubahnya lokasi atau tempat disebut teregionalisasi. Metode digunakan teregionalisasi kriging. ordinary kriging perlu memperhitungkan semivariogram. Hujan suatu proses jatuhnya air berasal dari awan ke bumi. di ukur memalui cura...

Journal: :journal of mining and environment 2011
h. rezaee o. asghari j.k. yamamoto

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...

Journal: :European Journal of Operational Research 2005
Jack P. C. Kleijnen Wim C. M. Van Beers

This paper investigates the use of Kriging in random simulation when the simulation output variances are not constant. Kriging gives a response surface or metamodel that can be used for interpolation. Because Ordinary Kriging assumes constant variances, this paper also applies Detrended Kriging to estimate a non-constant signal function, and then standardizes the residual noise through the hete...

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...

2006
Duanping Liao Donna J. Peuquet Yinkang Duan Eric A. Whitsel Jianwei Dou Richard L. Smith Hung-Mo Lin Jiu-Chiuan Chen Gerardo Heiss

Spatial estimations are increasingly used to estimate geocoded ambient particulate matter (PM) concentrations in epidemiologic studies because measures of daily PM concentrations are unavailable in most U.S. locations. This study was conducted to a) assess the feasibility of large-scale kriging estimations of daily residential-level ambient PM concentrations, b) perform and compare cross-valida...

Journal: :Advances in Engineering Software 2012
Ivo Couckuyt A. Forrester Dirk Gorissen Filip De Turck Tom Dhaene

When analysing data from computationally expensive simulation codes or process measurements, surrogate modelling methods are firmly established as facilitators for design space exploration, sensitivity analysis, visualisation and optimisation. Kriging is a popular surrogate modelling technique for data based on deterministic computer experiments. There exist several types of Kriging, mostly dif...

Journal: :JIPS 2015
Xuan Thanh Nguyen Ba Tung Nguyen Khac Phong Do Quang Hung Bui Thi Nhat Thanh Nguyen Van Quynh Vuong Thanh Ha Le

This paper presents the applications of Kriging spatial interpolation methods for meteorologic variables, including temperature and relative humidity, in regions of Vietnam. Three types of interpolation methods are used, which are as follows: Ordinary Kriging, Universal Kriging, and Universal Kriging plus Digital Elevation model correction. The input meteorologic data was collected from 98 grou...

2008
JON OLAV SKØIEN GERARD B. M. HEUVELINK EDZER J. PEBESMA E. J. PEBESMA

ABSTRACT Decision makers will in an emergency situation often be interested in predictions of harmful environmental variables relative to a certain threshold. We are therefore examining the robustness of different methods which are supposed to give unbiased estimates relative to such a threshold, both for point predictions and areal averages. We are also interested in exceedance probabilities. ...

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