A comparison of approximate response functions in structural reliability analysis
By C. Bucher, Thomas Most. 2008
169 citations recorded by the source corpus.
Subfields: Civil and Structural Engineering, Mechanics of Materials, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/093b9defa5cb5dfc0ed5f39a7a108ae857474988
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
In Mechanics of Materials
- Â. Teixeira
- Carlos Soares
- J. Mantari
- Huu-Tai Thai
- Trung‐Kien Nguyen
- Erasmo Carrera
- Ashraf M. Zenkour
- Thuc P. Vo
In Statistics and Probability
Citations in the corpus
- LIF: A new Kriging based learning function and its application to structural reliability analysis (2017, background): “Within recent years, different kinds of meta-models [3,11] are proposed to replace the target performance function.”
- Review and application of Artificial Neural Networks models in reliability analysis of steel structures (2015, methodology): “More recently, Bucher and Most [24] have applied these approximation methods to several examples of nonlinear structural analysis concluding that the relative accuracy of the various approaches depends on the specific problem under consideration.”