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Design of experiments is often used to better understand or improve the output measures of a simulation model. Traditional cuboidal and spherical designs have been effective when the factor input regions are known. However, often in practice, simulation models have additional stochastic constraints causing the input factor space to be restricted and irregularly shaped. This paper looks into several...
Random simulation with heterogeneous variance is a common phenomenon in real-world simulation cases. Most of the current meta-models assume homogeneous variances and hence are unable to provide satisfactory estimations of these models. This article presents a new kriging model with modified nugget effect, which accounts for heterogeneous variances in simulations. The new model can reduce the influence...
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