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- W2185165453 abstract "Abstract One approach to rapidly exploring large design spaces is to evaluate the performance of a small number of representative points in the space, then based on those points, construct an approximation to the response over a region of interest. Linear, piecewise linear, quadratic and multivariate adaptive regression splines (MARS) models are fit to an example 5-dimensional data set representative of information available in preliminary engineering design. When the number of data points representing a high-dimensional response is small, all of the approximation models appear to perform nearly equally." @default.
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- W2185165453 date "1999-09-12" @default.
- W2185165453 modified "2023-10-14" @default.
- W2185165453 title "Fitting Functions to Data in High Dimensional Design Space" @default.
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- W2185165453 doi "https://doi.org/10.1115/detc99/dac-8622" @default.
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