A combined sensitivity analysis and kriging surrogate modeling for early validation of health indicators

Mathematical Modeling for Volatile Organic Compounds Removal in a Biofilter: Model Validation and Sensitivity Analysis

A new surrogate modeling technique combining Kriging and polynomial chaos expansions - Application to uncertainty analysis in computational dosimetry

In numerical dosimetry, the recent advances in high performance computing led to a strong reduction of the required computational time to assess the specific absorption rate (SAR) characterizing the human exposure to electromagnetic waves. However, this procedure remains time-consuming and a single simulation can request several hours. As a consequence, the influence of uncertain input paramete...

Characterizing Uncertainty Attributable to Surrogate Models

This paper investigates the characterization of the uncertainty in the prediction of surrogate models. In the practice of engineering, where predictive models are pervasively used, the knowledge of the level of modeling error in any region of the design space is uniquely helpful for design exploration and model improvement. The lack of methods that can explore the spatial variation of surrogate...

Nonlinear disjunctive kriging for the estimating and modeling of a vein copper deposit

ABSTRACT Estimation of mineral resources and reserves with low values of error is essential in mineral exploration. The aim of this study is to estimate and model a vein type deposit using disjunctive kriging method. Disjunctive Kriging (DK) as an appropriate nonlinear estimation method has been used for estimation of Cu values. For estimation of Cu values and modelling of the distributio...

APPLICATION OF KRIGING METHOD IN SURROGATE MANAGEMENT FRAMEWORK FOR OPTIMIZATION PROBLEMS

In this paper, Kriging has been chosen as the method for surrogate construction. The basic idea behind Kriging is to use a weighted linear combination of known function values to predict a function value at a place where it is not known. Kriging attempts to determine the best combination of weights in order to minimize the error in the estimated function value. Because the actual function value...