國立高雄大學統計學研究所
98學年度書報討論題目暨摘要登記表
姓名：鄭榮憲
題目：Building Surrogate Models Based on Detailed and Approximate
Simulations
作者：Zhiguang Qian, Carolyn Conner Seepersad, V. Roshan Joseph,
Janet K. Allen, C.F. Jeff Wu
出處：Journal of Mechanical Design 128(4), 668-677, 2008
摘要：
Preliminary design of a complex system often involves exploring a broad
design space. This may require repeated use if computationally expensive
simulations. To ease the computational burden, surrogate models are built
to provide rapid approximations of more expensive models. However, the
surrogate models themselves are often expensive to build because they are
based on repeated experiments with computationally expensive simulations.
An alternative approach is to replace the detailed simulations with simplified
approximate simulations, thereby sacrificing accuracy for reduced computational time. Naturally, surrogate models which are built from these approximate simulations will also be imprecise. A strategy is needed for improving
the precision of surrogate models based on approximate simulations without
significantly increasing computational time. In this paper, a new approach is
integrating data from approximate and detailed simulations to build a surrogate model that describes the relationship between output parameters and
input parameters. Experimental results from approximate simulations form
the bulk of the data, and they are used to build a model based on a Gaussian
process. The fitted model is then ’adjusted’ by incorporating a small amount
of data from detailed simulations to get a more accurate prediction model.
The effectiveness of this approach is demonstrated with a design example
involving cellular materials for an electronics cooling application. The emphasis is on the method and not on the results per se.
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