We evaluate the performance and statistical accuracy of the fast Fourier transform method for unconditional and conditional simulation. The method is applied under difficult but realistic circumstances of a large field (1001 by 1001 points) with abundant conditioning criteria and a band limited, anisotropic, fractal-based statistical characterization (the von Kármán model). The simple Fourier u...

In this work, we investigate the issue of providing a statistical model for the response of a computer model-described nuclear engineering system, for use in uncertainty propagation. The motivation behind our approach is the need for providing an uncertainty assessment even in the circumstances where only a few samples are available. Building on our recent work in using a regression approach wi...

This paper is continuation work of a research started in 2005. In the previous research, variety of fuzzy digital elevation models was constructed and the best fit model was selected in order to present an alternative in modelling height information. The previous study revealed that fuzzy digital elevation model gave satisfied result compared with the result from TIN (Triangulated Irregular Net...

In this study, optimum combinations of available rainfall gauging stations are selected by a model which is consist of geo statistics model as an estimator  and an optimized model. At the  first,  watershed  is  approximated  to  several  regular  geometric  shapes.  Then  kriging calculates  the  variance &nbs...

In this work, the use of both a second-order response surface method (RSM) and the Kriging method as approximation models for design optimization are investigated and compared. After validating the accuracy of each method with simple one-and two-dimensional analytic functions, they are applied to two Supersonic Business Jet (SBJ) drag minimization design cases in order to obtain a clear compari...

Interpolating scattered data points is a problem of wide ranging interest. One of the most popular interpolation methods in geostatistics is ordinary kriging. The price for its statistical optimality is that the estimator is computationally very expensive. We demonstrate the space and time efficiency and accuracy of approximating ordinary kriging through the use of covariance tapering combined ...

In this paper, we implement and compare the accuracy of ordinary kriging, lognormal ordinary kriging, inverse distance weighting (IDW) and splines for interpolating seasonally stable soil properties (pH, electric conductivity and organic matter) that have been demonstrated to affect yield production. The choice of the exponent value for IDW and splines as well as the number of the closest neigh...

Resources/reserves classification is crucial for block model creation utilised in mine planning and feasibility study. Selection of estimation methods is an essential part of mineral exploration and mining activities. In other word, resources classification is an issue for mining companies, investors, financial institutions and authorities, but it remains subject to some confusion. The aim of t...

A new kriging predictor is proposed. It gives a better performance over the existing predictor when the constant mean assumption in the kriging model is unreasonable. Moreover, the new predictor seems to be robust to the misspecifications in the correlation parameters. The advantages of the new predictor is demonstrated using some examples from the computer experiments literature.