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Modified screening-based Kriging method with cross validation and application to engineering design

机译：基于修改的筛选克里格方法，交叉验证和工程设计应用

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In this paper, a basis screening Kriging method using cross validation error is proposed to alleviate computational burden of the dynamic Kriging while maintaining its accuracy. Metamodeling is widely used for design optimization of complex engineering applications where considerable computation time is required. The Kriging method is one of popular metamodeling methods due to its accuracy and efficiency. There have been many attempts to improve accuracy of the Kriging method, and the dynamic Kriging method using cross-validation error, which selects adequate basis functions to best describe the mean structure of a response using a genetic algorithm, achieves outstanding performance in terms of accuracy. However, despite its accuracy, the dynamic Kriging requires very large amounts of computation because of the genetic algorithm and no limitation for order of basis functions. In the proposed method, a basis function set is determined by screening each basis function instead of using the genetic algorithm, which has advantages in computation for high dimensional metamodels or repeated metamodel generation. Numerical studies with four mathematical examples and two engineering applications verify that the proposed basis screening Kriging significantly reduces computation time with similar accuracy as the dynamic Kriging. (C) 2019 Elsevier Inc. All rights reserved.
机译：在本文中，提出了使用交叉验证误差的基础筛选方法，以减轻动态Kriging的计算负担，同时保持其精度。 Metomodeling广泛用于复杂工程应用的设计优化，其中需要相当大的计算时间。由于其准确性和效率，Kriging方法是流行的元模型方法之一。已经有许多尝试提高Kriging方法的准确性，并且使用交叉验证误差的动态Kriging方法选择适当的基本功能，以最能描述使用遗传算法的响应的平均结构，在准确性方面取得出色的性能。然而，尽管它准确性，动态克里格由于遗传算法而要求非常大的计算，而是对基函数的顺序没有限制。在所提出的方法中，通过筛选每个基函数而不是使用遗传算法来确定基函数集，该函数在计算高维元区或重复的元模型生成中具有优点。具有四种数学例子和两个工程应用的数值研究验证了所提出的基础筛查Kriging显着减少了与动态克里格相似的准确性的计算时间。 （c）2019 Elsevier Inc.保留所有权利。

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