A D-Optimal Sequential Calibration Design for Computer Models

Huaimin Diao, Yan Wang, Dianpeng Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
Plum Print visual indicator of research metrics
  • Citations
    • Citation Indexes: 3
  • Captures
    • Readers: 1
  • Social Media
    • Shares, Likes & Comments: 19
see details

Abstract

The problem with computer model calibration by tuning the parameters associated with computer models is significant in many engineering and scientific applications. Although several methods have been established to estimate the calibration parameters, research focusing on the design of calibration parameters remains limited. Therefore, this paper proposes a sequential computer experiment design based on the D-optimal criterion, which can efficiently tune the calibration parameters while improving the prediction ability of the calibrated computer model. Numerical comparisons of the simulated and real data demonstrate the efficiency of the proposed technique.

Original languageEnglish
Article number1375
JournalMathematics
Volume10
Issue number9
DOIs
Publication statusPublished - 1 May 2022

Keywords

  • calibration
  • computer models
  • fisher information
  • sequential D-optimal
  • surrogate model

Fingerprint

Dive into the research topics of 'A D-Optimal Sequential Calibration Design for Computer Models'. Together they form a unique fingerprint.

Cite this

Diao, H., Wang, Y., & Wang, D. (2022). A D-Optimal Sequential Calibration Design for Computer Models. Mathematics, 10(9), Article 1375. https://doi.org/10.3390/math10091375