Efficient Response Surface Modeling by Using Moving Least-Squares Method and Sensitivity

By Chwail Kim, Semyun Wang, Kyung K. Choi. 2005

101 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computational Theory and Mathematics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/b3f774f7630c013f1447b5f5af22a406f18e28f7

How researchers see this paper

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

In Civil and Structural Engineering

1. Donald H. Burn
2. Andy J. Keane
3. Bryan Tolson
4. Alexander I. J. Forrester
5. Saman Razavi
6. George Stefanou

In Computational Theory and Mathematics

1. Alexander I. J. Forrester
2. Saman Razavi
3. Donald H. Burn
4. Bryan Tolson
5. Andy J. Keane
6. Yaochu Jin
7. Peter I. Frazier
8. Benjamin Peherstorfer

In Management Science and Operations Research

1. Alexander I. J. Forrester
2. Saman Razavi
3. Donald H. Burn
4. Bryan Tolson
5. Andy J. Keane
6. Enrico Camporeale
7. G. Em Karniadakis
8. David Ginsbourger

Citations in the corpus

• Recent advances in surrogate-based optimization (2009, methodology): “[48] have presented a gradient enhanced MLS method.”
• Metamodeling in Multidisciplinary Design Optimization: How Far Have We Really Come? (2014, unknown): “least squares [77–79].”
• Review of surrogate modeling in water resources (2012, methodology): “Koch et al. [1999] demonstrate that in order to obtain a reasonably accurate second-order polynomial, the minimum number of design sites may not be sufficient and suggest that 4.”