仿真模型的灵敏度分析

J. Kleijnen
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引用次数: 19

摘要

这篇文章概述了模拟模型的敏感性分析,包括梯度的估计。它涵盖了经典设计及其相应的(元)模型;即,一阶多项式元模型的分辨率iii设计包括分数析因两水平设计,增强了两因素相互作用的元模型的分辨率iv和分辨率v设计,以及二阶多项式元模型的设计包括中心复合设计。它还回顾了具有非常多因素的仿真模型的因素筛选,重点是所谓的“顺序分岔”方法。此外,还回顾了Kriging元模型及其设计。文中提到,灵敏度分析还可以针对仿真系统的优化,允许多个随机仿真输出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sensitivity Analysis of Simulation Models
This contribution presents an overview of sensitivity analysis of simulation models, including the estimation of gradients. It covers classic designs and their corresponding (meta)models; namely, resolution-III designs including fractional-factorial two-level designs for first-order polynomial metamodels, resolution-IV and resolution-V designs for metamodels augmented with two-factor interactions, and designs for second-degree polynomial metamodels including central composite designs. It also reviews factor screening for simulation models with very many factors, focusing on the so-called "sequential bifurcation" method. Furthermore, it reviews Kriging metamodels and their designs. It mentions that sensitivity analysis may also aim at the optimization of the simulated system, allowing multiple random simulation outputs.
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