Abstract
Kriging is a useful method for developing metamodels for product design optimization. The most popular kriging method, known as ordinary kriging, uses a constant mean in the model. In this article, a modified kriging method is proposed, which has an unknown mean model. Therefore, it is called blind kriging. The unknown mean model is identified from experimental data using a Bayesian variable selection technique. Many examples are presented, which show remarkable improvement in prediction using blind kriging over ordinary kriging. Moreover, a blind kriging predictor is easier to interpret and seems to be more robust against mis-specification in the correlation parameters.
| Original language | English (US) |
|---|---|
| Article number | 031102 |
| Journal | Journal of Mechanical Design, Transactions of the ASME |
| Volume | 130 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2008 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Mechanics of Materials
- Mechanical Engineering
- Computer Science Applications
- Computer Graphics and Computer-Aided Design
Keywords
- Computer experiments
- Cross validation
- Design optimization
- Finite element models
- Kriging
- Metamodels
- Variable selection