Hierarchical Kriging Model for Variable-Fidelity Surrogate Modeling

By Zhonghua Han, Stefan Görtz. 2012

408 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/90dabb8fa8baed19d8de471ebebda98254468c42

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Juan José Palacios Alonso
2. William D. Gropp
3. David L. Darmofal
4. Joaquim R. Martins

In Statistics and Probability

1. Juan José Palacios Alonso
2. William D. Gropp
3. David L. Darmofal
4. Joaquim R. Martins

Citations in the corpus

• CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences (2014, methodology): “Techniques for building large-scale flexible databases are in their infancy, and range from simple software infrastructures that manage large numbers of simulation jobs to more sophisticated reduced-order models,(138) surrogate models, and Kriging methods.(102,103) The objective of a research thrust”