Location fingerprinting suffers in dynamic environments and needs recalibration from time to time to maintain system performance. This paper proposes an adaptive approach for location fingerprinting. Based on real-time received signal strength indicator (RSSI) samples measured by a group of reference devices, the approach applies a modified Universal Kriging (UK) interpolant to estimate adaptiv...

The work deals with the application of Support Vector Machines (SVM) for environmental and pollution spatial data analysis and modeling. The main attention is paid to classification of spatially distributed data with SVM and comparison with probabilistic mapping using nonparametric geostatistical model (indicator kriging). SVMs with RBF kernels were used. It is shown that optimal bandwidth of k...

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 ...

Many satellite images have a spatial resolution coarser than the extent of land cover patterns on the ground, leading to mixed pixels whose composite spectral response consists of responses from multiple land cover classes. Spectral unmixing procedures only determine the fractions of such classes within a coarse pixel without locating them in space. Super-resolution or sub-pixel mapping aims at...

spatial and temporal distribution of qualitative factors of groundwaters is important to preserve their quality. so, one of the advanced techniques for distribution of groundwater’s qualitative is geostatistic methods. in this study, 33 active wells were randomly sampled to determine the spatial distribution of nitrate pollution in groundwater of the siakh darengoun region (west of shiraz in fa...

Finite element analyses of irregular structures require adaptive mesh refinement to achieve more accurate results in an efficient manner. This is also true for a non-conventional finite method with Kriging interpolation, called the Kriging-based (K-FEM). paper presents study automatic meshing procedures two-dimensional linear elasticity problems using K-FEM. The Matlab Partial Differential Equa...

This paper demonstrates the application of correlated Gaussian process based approximations to optimization where multiple levels of analysis are available, using an extension to the geostatistical method of co-kriging. An exchange algorithm is used to choose which points of the search space to sample within each level of analysis. The derivation of the co-kriging equations is presented in an i...

Metamodeling has been widely used for design optimization by building surrogate models for computationally intensive engineering application problems. Among all the metamodeling methods, the kriging method has gained significant interest for its accuracy.However, in traditional krigingmethods, themean structure is constructed using a fixed set of polynomial basis functions, and the optimization...

In this paper we study the ability of the Cokriging method to represent functions with multiple local minima and sharp discontinuities for use in the multidimensional design of a low-boom supersonic business jet wing-body-canard configuration. Cokriging approximation models are an extension of the original Kriging method which incorporate secondary information such as the values of the gradient...

The aim of this paper is to compare four different methods for binary classification with an underlying Gaussian process with respect to theoretical consistency and practical performance. Two of the inference schemes, namely classical indicator kriging and simplicial indicator kriging, are analytically tractable and fast. However, these methods rely on simplifying assumptions which are inapprop...