Kriging-based exploration strategies often rely on a single Ordinary Kriging model which parametric covariance kernel is selected a priori or on the basis of an initial data set. Since choosing an unadapted kernel can radically harm the results, we wish to reduce the risk of model misspecification. Here we consider the simultaneous use of multiple kernels within Kriging. We give the equations o...

We report an intelligent image restoration approach by combining the geostatistical interpolation technique of punctual kriging and the machine learning approach of adaptive learning. Digital images degraded from Gaussian white noise are restored by first utilizing fuzzy logic for selecting pixels that need to be kriged. The concept of punctual kriging is then used to estimate the intensity of ...

Uncertainties in biological tissue properties are weighed in the case of an hyperthermia calculation. Stochastic spectral and collocation methods are applied to analyze the impact of these uncertainties on the distribution of the electromagnetic power absorbed inside the body of a patient. They enable to realize sensitivity and uncertainty analyses more efficiently than when using a two level e...

• We propose a Bayesian inversion method combining adaptive Polynomial Chaos Kriging and Structural Reliability Method. An active-learning scheme is proposed in order to enrich the surrogate models informative zones. The illustrated on three inverse problems with different complexity dimensionality. enables efficiently sample from posteriors distributions for limited amount of model calls. In t...

Remote sensing can be fruitfully used in the characterization of metals within stockpiles and tailings, produced from mining activities. Satellite information, form band ratio, act as an auxiliary variable, with a certain correlation ground primary data. In presence this modeled nested structures, spatial components without filtered out, so that useful data grows. This paper investigates possib...

The metamodeling has been widely used for design optimization problems by building surrogate models for compute-intensive simulation models. Among metamodeling methods, the Kriging method has gained significant interest for its accuracy in developing the surrogate model. However, in traditional Kriging methods, the optimization methods that are used to obtain the optimum correlation parameter d...

drought monitoring is a fundamental component of drought risk management. it is normally performed usingvarious drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables.in many instances, drought indices are used for monitoring purposes. geostatistical methods allow the interpolationof spatially referenced data and the prediction of values fo...