This paper proposes a novel method to select an experimental design for interpolation in simulation.Though the paper focuses on Kriging in deterministic simulation, the method also applies to other types of metamodels (besides Kriging), and to stochastic simulation.The paper focuses on simulations that require much computer time, so it is important to select a design with a small number of observations.The proposed method is therefore sequential.The novelty of the method is that it accounts for the specific input/output function of the particular simulation model at hand; i.e., the method is application-driven or customized.This customization is achieved through cross-validation and jackknifing.The new method is tested through two academic ...
Metamodels approximate complex multivariate data sets from simulations and experiments. These data s...
Nowadays it is common to reproduce physical systems using mathematical simulation models and, despit...
<p>In this article we propose an adaptive two-stage dual metamodeling approach for stochastic simula...
This paper proposes a novel method to select an experimental design for interpolation in random simu...
This paper proposes a novel method to select an experimental design for interpolation in random simu...
This paper proposes a novel method to select an experimental design for interpolation in random simu...
Many scientific disciplines use mathematical models to describe complicated real systems. Often, ana...
This tutorial reviews the design and analysis of simulation experiments. These experiments may have ...
This article reviews the design and analysis of simulation experiments. It focusses on analysis via ...
This article reviews Kriging (also called spatial correlation modeling). It presents the basic Krigi...
We extend the basic theory of kriging, as applied to the design and analysis of deterministic comput...
Processes are so complex in many areas of science and technology that physical experimentation is of...
This chapter surveys two methods for the optimization of real-world systems that are modelled throug...
International audienceMetamodeling is getting more and more widespread in the domain of electromagne...
Simulation models are used in many fields to experiment with real-world systems to gain insight into...
Metamodels approximate complex multivariate data sets from simulations and experiments. These data s...
Nowadays it is common to reproduce physical systems using mathematical simulation models and, despit...
<p>In this article we propose an adaptive two-stage dual metamodeling approach for stochastic simula...
This paper proposes a novel method to select an experimental design for interpolation in random simu...
This paper proposes a novel method to select an experimental design for interpolation in random simu...
This paper proposes a novel method to select an experimental design for interpolation in random simu...
Many scientific disciplines use mathematical models to describe complicated real systems. Often, ana...
This tutorial reviews the design and analysis of simulation experiments. These experiments may have ...
This article reviews the design and analysis of simulation experiments. It focusses on analysis via ...
This article reviews Kriging (also called spatial correlation modeling). It presents the basic Krigi...
We extend the basic theory of kriging, as applied to the design and analysis of deterministic comput...
Processes are so complex in many areas of science and technology that physical experimentation is of...
This chapter surveys two methods for the optimization of real-world systems that are modelled throug...
International audienceMetamodeling is getting more and more widespread in the domain of electromagne...
Simulation models are used in many fields to experiment with real-world systems to gain insight into...
Metamodels approximate complex multivariate data sets from simulations and experiments. These data s...
Nowadays it is common to reproduce physical systems using mathematical simulation models and, despit...
<p>In this article we propose an adaptive two-stage dual metamodeling approach for stochastic simula...