Skip to content
Journal article

Use of Kriging Models to Approximate Deterministic Computer Models

Martin J, Simpson T ...see all

AIAA Journal, vol. 43, issue 4 (2005) pp. 853-863

  • 161

    Readers

    Mendeley users who have this article in their library.
  • 70

    Citations

    Citations of this article.
  • N/A

    Views

    ScienceDirect users who have downloaded this article.
Sign in to save reference

Abstract

The use of kriging models for approximation and metamodel-based design and optimization has been steadily on the rise in the past decade. The widespread use of kriging models appears to be hampered by 1) computationally efficient algorithms for accurately estimating the models parameters, 2) an effective method to assess the resulting models quality, and 3) the lack of guidance in selecting the appropriate form of the kriging model.We attempt to address these issues by comparing 1) maximum likelihood estimation and cross validation parameter estimation methods for selecting a kriging models parameters given its form and 2) an R2 of prediction and the corrected Akaike information criterion assessment methods for quantifying the quality of the created kriging model. These methods are demonstrated with six test problems. Finally, different forms of kriging models are examined to determine if more complex forms are more accurate and easier to fit than simple forms of kriging models for approximating computer models.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Get full text

Authors

  • Jay D. Martin

  • Timothy W. Simpson

Cite this document

Choose a citation style from the tabs below