Adaptive Designs of Experiments for Accurate Approximation of a Target Region

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Reliability-based design optimization using kriging surrogates and subset simulation (2011, methodology): “, 1998) or for probability/quantile estimation (Oakley, 2004; Bichon et al., 2008; Lee and Jung, 2008; Ranjan et al., 2008; Vazquez and Bect, 2009; Picheny et al., 2010).”
Sequential design of computer experiments for the estimation of a probability of failure (2010, methodology): “The targeted IMSE proposed in Picheny et al. (2010) is a modification of the IMSE (Integrated Mean Square Error) sampling criterion (Sacks et al., 1989). While the IMSE sampling criterion computes the average of the kriging variance (over a compact domain X) in order to achieve a space-filling desig”
Design of computer experiments: space filling and beyond (2011, neutral): “Picheny et al (2010) induce it by focussing their attention towards particular target regions.”
A new adaptive response surface method for reliability analysis (2013, background): “Recent contributions have been made on kriging [37,14,4] and support vector machine”
LIF: A new Kriging based learning function and its application to structural reliability analysis (2017, methodology): “Various kinds of sequential DoE based on the Kriging model have been proposed to improve the accuracy of structural reliability analysis and reduce the number of calls to the real performance function [8,29,32,38,41,42].”