Monte Carlo algorithms for evaluating Sobol' sensitivity indices
Monte Carlo algorithms for evaluating Sobol' sensitivity indices
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DOI：
10.1016/j.matcom.2009.09.005
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发表时间：
2010-11-01
影响因子：
4.6
通讯作者：
Georgieva, R.
中科院分区：
文献类型：
--
作者：
Dimov, I.;Georgieva, R.
灵敏度分析是一种用于确定模型的鲁棒性、可靠性和效率的强大技术。在这个过程中的主要问题是评估总的敏感性指标，衡量一个参数的主要影响和所有的相互作用，涉及该参数。从数学的角度来看，这个问题是由一组多维积分。在这项工作中，一个简单的自适应Monte Carlo技术评估Sobol的敏感性指标。简单的蒙特卡罗和自适应蒙特卡罗算法的精度和复杂性的比较。数值实验评价不同的维度的积分。(C)2009年由Elsevier B.V.代表IMACS出版。
Sensitivity analysis is a powerful technique used to determine robustness, reliability and efficiency of a model. The main problem in this procedure is the evaluating total sensitivity indices that measure a parameter's main effect and all the interactions involving that parameter. From a mathematical point of view this problem is presented by a set of multidimensional integrals. In this work a simple adaptive Monte Carlo technique for evaluating Sobol' sensitivity indices is developed. A comparison of accuracy and complexity of plain Monte Carlo and adaptive Monte Carlo algorithms is presented. Numerical experiments for evaluating integrals of different dimensions are performed. (C) 2009 Published by Elsevier B.V. on behalf of IMACS.