Comparative studies of metamodeling techniques under multiple modeling criteria

Ruichen Jin, Wei Chen, Timothy W. Simpson

Research output: Contribution to conferencePaper

92 Scopus citations

Abstract

Despite the advances in computer capacity, the enormous computational cost of complex engineering simulations makes it impractical to rely exclusively on simulation for the purpose of design optimization. To cut down the cost, surrogate models, also known as metamodels, are constructed from and then used in lieu of the actual simulation models. In the paper, we systematically compare four popular metamodeling techniques-Polynomial Regression, Multivariate Adaptive Regression Splines, Radial Basis Functions, and Kriging-based on multiple performance criteria using fourteen test problems representing different classes of problems. Our objective in this study is to investigate the advantages and disadvantages these four metamodeling techniques using multiple modeling criteria and multiple test problems rather than a single measure of merit and a single test problem.

Original languageEnglish (US)
DOIs
StatePublished - 2000
Event8th Symposium on Multidisciplinary Analysis and Optimization 2000 - Long Beach, CA, United States
Duration: Sep 6 2000Sep 8 2000

Other

Other8th Symposium on Multidisciplinary Analysis and Optimization 2000
CountryUnited States
CityLong Beach, CA
Period9/6/009/8/00

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Mechanical Engineering

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    Jin, R., Chen, W., & Simpson, T. W. (2000). Comparative studies of metamodeling techniques under multiple modeling criteria. Paper presented at 8th Symposium on Multidisciplinary Analysis and Optimization 2000, Long Beach, CA, United States. https://doi.org/10.2514/6.2000-4801