Directing to the high cost of computer simulation optimization problem, Kriging surrogate model is widely used to decrease the computation time. Since the sequential Kriging optimization is time consuming, this article extends the expected improvement and put forwards a modified sequential Kriging optimization (MSKO). This method changes the twice optimization problem into once by adding more t...

Sensitivity analysis of capital investments can be effectively carried out by employing a metamodel approach and experimental designs. Although polynomial regression metamodels are popular and straightforward, they do not consider spatial relationships among the data. Dual kriging is an estimation technique that allows the incorporation of spatial correlation into the interpolation or estimatio...

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. ...

Kriging is a spatial interpolation algorithm which provides the best unbiased linear prediction of an observed phenomena by taking a weighted average of samples within a neighbourhood. It is widely used in areas such as geo-statistics where, for example, it may be used to predict the quality of mineral deposits in a location based on previous sample measurements. Kriging has been identified as ...

Probability maps are used to define areas with high and low certainty of exceeding a threshold value. The most popular methods for creating these maps are variants of indicator kriging. However, such methods are questionable when the data exhibit a trend or contain measurement errors, the latter of which is common in most data sets. This paper presents an alternative approach that maps the risk...

Ionospheric delay effect is a critical issue that limits the accuracy of precise Global Navigation Satellite System (GNSS) positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where variations in the ionosphere are larger. Kriging spatial interpolation techniques have been recently introduced to model the spatial correlation and variability of ionos...

estimation of gold reserves and resources has been of interest to mining engineers and geologists for ages. the existence of outlier values shows the economic part of the deposits subject to the fact that don’t depend on the human or technical errors. the presence of these high values causes a pseudo dramatically increment in variance estimation of economical blocks when applying conventional m...

In simulation, Median Polish Kriging is a technique used to predict unobserved data points in two-dimensional space. The linear behavior of the traditional Median Polish Kriging in the estimation of the mean function in a high grid makes the interpolation of O(1) which has a low order in the prediction and that leads to a high prediction error. Therefore, an improvement in the estimation of the...

Kriging interpolation is largely used in geostatistics to characterise the spatial structure of data and it is established in general based upon the stationary or intrinsic assumptions; however, the consequence of this second-order approximation is that the local singularities (or extremes) could be smoothed off. This drawback could be magnified as a finerscale phenomenon is being investigated,...

Kriging (Gaussian process, spatial correlation) metamodels approximate the Input/Output (I/O) functions implied by the underlying simulation models; such metamodels serve sensitivity analysis and optimization, especially for computationally expensive simulations. In practice, simulation analysts often know that the I/O function is monotonic. To obtain a Kriging metamodel that preserves this kno...