An effective screening design for sensitivity analysis of large models
An effective screening design for sensitivity analysis of large models
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DOI：
10.1016/j.envsoft.2006.10.004
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发表时间：
2007-10-01
影响因子：
4.9
通讯作者：
Saltelli, Andrea
中科院分区：
文献类型：
--
作者：
Campolongo, Francesca;Cariboni, Jessica;Saltelli, Andrea
1991年，Morris提出了一种有效的筛选敏感性度量方法，用于识别多因素模型中的少数重要因素。该方法是基于计算每个输入的一些增量比率，即基本效果，然后平均评估输入的整体重要性。尽管它的价值，该方法仍然很少使用，而不是当地的分析变化的一个因素，在一个基线point.In这一块的工作，我们提出了一个修订版的基本效果的方法，改进的措施和抽样策略的定义。在目前的形式的方法共享许多积极的品质的方差为基础的技术，具有较低的计算成本的优势，所示的分析examples.该方法被用来评估的敏感性的化学反应模型的二甲基硫（DMS），气体参与气候变化。敏感性分析的结果为重新考虑模型提供了基础：模型的某些组成部分可能需要更彻底的建模工作，而其他一些组成部分可能需要简化。(c)2006爱思唯尔有限公司保留所有权利。
In 1991 Morris proposed an effective screening sensitivity measure to identify the few important factors in models with many factors. The method is based on computing for each input a number of incremental ratios, namely elementary effects, which are then averaged to assess the overall importance of the input. Despite its value, the method is still rarely used and instead local analyses varying one factor at a time around a baseline point are usually employed.In this piece of work we propose a revised version of the elementary effects method, improved in terms of both the definition of the measure and the sampling strategy. In the present form the method shares many of the positive qualities of the variance-based techniques, having the advantage of a lower computational cost, as demonstrated by the analytical examples.The method is employed to assess the sensitivity of a chemical reaction model for dimethylsulphide (DMS), a gas involved in climate change. Results of the sensitivity analysis open up the ground for model reconsideration: some model components may need a more thorough modelling effort while some others may need to be simplified. (c) 2006 Elsevier Ltd. All rights reserved.