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An Efficient Approach for Uncertainty Analysis in Multidisciplinary Design Optimization

机译:多学科设计优化中不确定性分析的有效方法

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In this paper, an efficient multidisciplinary design optimization method based on evidence theory is proposed. Evidence theory is used to quantify uncertainty in terms of uncertainty measures of belief and plausibility. Since uncertainty measures provided by evidence theory are discontinuous functions, the response surface is utilized to obtain smooth functions so that the traditional gradient-based algorithms can be used in optimization.
机译:本文提出了一种基于证据理论的高效多学科设计优化方法。证据理论用于量化信仰和合理性的不确定性措施的不确定性。由于证据理论提供的不确定性措施是不连续的功能,因此利用响应面来获得平滑的功能,以便可以在优化中使用传统的梯度基算法。

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