Comparison of the radial basis function and ordinary kriging model in the design of dynamic systems

Turuna S. Seecharan, Gordon J. Savage

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Metamodels such as radial basis functions (RBF) and Kriging models are becoming popular techniques for approximating complex mechanistic models. In the case of robust design where the design space is investigated for the best design parameters of the design variables, metamodels offer a fast and simple method since they can be easily applied to Monte Carlo methods. Most research in the area of metamodels compares the performance of the metamodel in approximating the existing mechanistic model. Much research looks at the performance of regression models with either Kriging or RBFs in their ability to approximate the mechanistic model. This paper will observe the performance of the radial basis function (RBF) with Kriging models in terms of the sustainable design of a dynamic system where design is performed using a Monte Carlo simulation (MCS).

Original languageEnglish (US)
Title of host publicationProceedings - 16th ISSAT International Conference on Reliability and Quality in Design
Pages408-412
Number of pages5
StatePublished - Dec 1 2010
Event16th ISSAT International Conference on Reliability and Quality in Design - Washington, DC, United States
Duration: Aug 5 2010Aug 7 2010

Other

Other16th ISSAT International Conference on Reliability and Quality in Design
CountryUnited States
CityWashington, DC
Period8/5/108/7/10

Keywords

  • Kriging model
  • Latin Square Design
  • Monte Carlo Simulation (MCS)
  • Radial Basis Functions (RBF)
  • Singular Value Decomposition (SVD)

Fingerprint Dive into the research topics of 'Comparison of the radial basis function and ordinary kriging model in the design of dynamic systems'. Together they form a unique fingerprint.

Cite this