Sequential Design with Mutual Information for Computer Experiments (MICE): Emulation of a Tsunami Model
Sequential Design with Mutual Information for Computer Experiments (MICE): Emulation of a Tsunami Model
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DOI：
10.1137/140989613
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发表时间：
2016-01-01
影响因子：
2
通讯作者：
Guillas, Serge
中科院分区：
文献类型：
--
作者：
Beck, Joakim;Guillas, Serge
计算机模拟器可以是计算密集型的，以运行大量的输入值，如优化和各种不确定性量化任务所需。计算机实验设计和分析的标准范例是采用高斯随机场来模拟计算机模拟器。高斯过程模型在从各种输入值的模拟运行中获得的输入-输出数据上进行训练。按照这种方法，我们提出了一个顺序设计算法MICE（互信息计算机实验），自适应地选择输入值，以运行计算机模拟器，以最大限度地提高预期的信息增益（互信息）在输入空间。与其他算法相比，MICE算法的上级计算效率通过测试函数和海啸模拟器证明，在这种情况下，总体增益高达20%。
Computer simulators can be computationally intensive to run over a large number of input values, as required for optimization and various uncertainty quantification tasks. The standard paradigm for the design and analysis of computer experiments is to employ Gaussian random fields to model computer simulators. Gaussian process models are trained on input-output data obtained from simulation runs at various input values. Following this approach, we propose a sequential design algorithm MICE (mutual information for computer experiments) that adaptively selects the input values at which to run the computer simulator in order to maximize the expected information gain (mutual information) over the input space. The superior computational efficiency of the MICE algorithm compared to other algorithms is demonstrated by test functions and by a tsunami simulator with overall gains of up to 20% in that case.