Classic Types of Surrogate Models
The polynomial response surface (PRS) methodology is a statistical technique that uses regression analysis and analysis of variance to determine the relationship between design variables and responses. A linear polynomial is used to approximate the implicit limit state equation. The coefficients of the linear polynomial are determined through experimental design.
- Audet C, Denni J, Moore D, Booker A, Frank P (2000) A surrogate-model-based method for constrained optimization. In: 8th symposium on multidisciplinary analysis and optimization, p 4891Google Scholar
- Desautels T, Krause A, Burdick J (2014) Parallelizing exploration-exploitation tradeoffs in Gaussian process bandit optimization. 15:3873–3923Google Scholar
- Sasena MJ, Papalambros P, Goovaerts P (2002) Exploration of metamodeling sampling criteria for constrained global optimization. 34:263–278Google Scholar
- Zheng J, Li Z, Gao L, Jiang G (2016) A parameterized lower confidence bounding scheme for adaptive metamodel-based design optimization. 33:2165–2184Google Scholar