In this paper we address two issues common to the analysis of large spatial datasets. One is the modeling of non-stationarity, and the other is the computational challenges in doing likelihood based estimation and kriging prediction. We model the spatial process as a convolution of independent Gaussian processes, with the spatially varying kernel function given by the modified Bessel functions....

nowadays, much attention has been paid on using geostatistical methods for estimation of spatial parameters, either using the variables of these parameters (kriging) or auxiliary variables (cokriging), in water and soil sciences. the quality of ground water for agriculture is very important; however, it is expensive and time consuming to measure parameters such as sar, na, ca, th, tds and ec. t...

A kriging modeling method is proposed to conduct the temperature uncertainty analysis of an injection mechanism in squeeze casting. A mathematical model of temperature prediction with multi input and single output is employed to estimate the temperature spatiotemporal distributions of the injection mechanism. The kriging model applies different weights to the independent variables according to ...

In many pharmaceutical process operations, first-principle models describing the behavior of the processed powders are difficult to derive or computationally very expensive and thus can be considered as “black-box” processes. Kriging is an efficient data-driven methodology that has been shown previously to predict steady-state operation of black-box processes while providing error estimates for...

This paper develops a simulation optimization algorithm based on Taylor Kriging and evolutionary algorithm (SOAKEA) for simulation models with high computational expenses. In SOAKEA, an evolutionary algorithm is used to search for optimal solutions of a simulation model, and Taylor Kriging temporarily serves as a surrogate fitness function of this evolutionary algorithm to evaluate solutions. T...

accurate knowledge of spatial distribution of soil physical and chemical properties is needed for suitable management and proper use of rangelands in masileh plain, qom, iran. in present study, for the spatial modeling of chemical and physical parameters such as sodium (na), calcium (ca), soluble potassium (k), magnesium (mg), electrical conductivity (ec), saturation percentage (sp%), silt, cla...

The effectiveness of surrogate based optimization of helicopter rotor blades for vibration reduction using kriging global approximations is investigated. The search for the optimal design is conducted using two methods: (1) the “one-shot” approach in which the surrogate is optimized directly and (2) a method based on the expected improvement function which seeks to find optimal designs while re...

In spatial data modelling and analysis there are a variety of techniques to perform prediction. The goal of these techniques is to take spatially located data and to establish estimates of data values at unknown locations. Of these techniques, the attractive aspects of kriging are often overshadowed by the slow speed of the calculation. Unfortunately the calculations necessary to perform krigin...