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Comparative study on influencing factors in adaptive metamodeling

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Abstract

In this research, influences of two factors in adaptive metamodeling, noise level of samples and initial size of samples, are investigated through comparative study. Two cases of adaptive metamodeling considering the best output point for optimization and the best fit in a specific output parameter space are considered. Three different metamodels, kriging, radial basis function, and multivariate polynomial, are employed in this study. Various test functions are used to create the sample data and evaluate the quality and efficiency of the adaptive metamodeling methods considering influences of noise and initial size of samples. The results of this research provide guidelines for selecting appropriate adaptive metamodeling methods to solve various engineering problems. Effectiveness of the developed guidelines has been demonstrated through case study applications.

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Acknowledgments

The authors would like to acknowledge the support from the Natural Sciences and Engineering Research Council (NSERC) of Canada through its Discovery Grant.

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Authors and Affiliations

  1. Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, AB, T2N 1N4, Canada

    Qinwen Yang & Deyi Xue

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  1. Qinwen Yang
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  2. Deyi Xue
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Correspondence to Deyi Xue.

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Yang, Q., Xue, D. Comparative study on influencing factors in adaptive metamodeling. Engineering with Computers 31, 561–577 (2015). https://doi.org/10.1007/s00366-014-0358-x

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  • DOI: https://doi.org/10.1007/s00366-014-0358-x

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