Variance-based sensitivity analysis of model outputs using surrogate models
Variance-based sensitivity analysis of model outputs using surrogate models
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DOI：
10.1016/j.envsoft.2011.01.002
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发表时间：
2011-06
期刊：
影响因子：
--
通讯作者：
D. Shahsavani;A. Grimvall
中科院分区：
文献类型：
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作者：
D. Shahsavani;A. Grimvall
如果一个计算机模型在不同的输入下运行多次，所获得的结果通常可以用来导出原始计算机代码的计算成本更低的近似值或代理模型。此后，可以采用代理模型来降低模型输出的基于方差的灵敏度分析（VBSA）的计算成本。在这里，我们提请注意一个程序，在该程序中，采用自适应序贯设计来获得代理模型和估计灵敏度指数为不同的子组的输入。这样的分组VBSA的结果然后用于选择最终VBSA的输入。我们的程序是特别有用的，当有一点先验知识的响应面，其目的是探索全局变化和局部非线性特征的模型输出。我们的结论是基于计算机实验，涉及基于过程的流域模型INCA-N，其中输出，如平均年河流氮负荷可以被视为19个模型参数的函数。
If a computer model is run many times with different inputs, the results obtained can often be used to derive a computationally cheaper approximation, or surrogate model, of the original computer code. Thereafter, the surrogate model can be employed to reduce the computational cost of a variance-based sensitivity analysis (VBSA) of the model output. Here, we draw attention to a procedure in which an adaptive sequential design is employed to derive surrogate models and estimate sensitivity indices for different sub-groups of inputs. The results of such group-wise VBSAs are then used to select inputs for a final VBSA. Our procedure is particularly useful when there is little prior knowledge about the response surface and the aim is to explore both the global variability and local nonlinear features of the model output. Our conclusions are based on computer experiments involving the process-based river basin model INCA-N, in which outputs like the average annual riverine load of nitrogen can be regarded as functions of 19 model parameters.