A response surface method based on weighted regression for structural reliability analysis

By Irfan Kaymaz, C. McMahon. 2005

302 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Mechanics of Materials, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7ad7bb57d5a5c654a4ec5bb0f4edec0037b675c2

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. Zhaoyang Lv
2. Hongzhong Huang
3. Pan Wang
4. N. Xiao
5. Zhenzhou Lu
6. Zhonglai Wang

In Mechanics of Materials

1. Zhaoyang Lv
2. Hongzhong Huang
3. Pan Wang
4. N. Xiao
5. Zhenzhou Lu
6. Zhonglai Wang

In Statistics and Probability

1. Zhaoyang Lv
2. Hongzhong Huang
3. Yu Pang
4. Pan Wang
5. N. Xiao
6. Zhenzhou Lu
7. Liping He
8. Zhonglai Wang

Citations in the corpus

• Reliability sensitivity analysis for structural systems in interval probability form (2011, methodology): “The following expression is suitable to obtain the weight for each sample point (Kaymaz and Mcmahon 2005)”
• A new learning function for Kriging and its applications to solve reliability problems in engineering (2015, methodology): “It is called metamodel with various kinds: Quadratic Response Surfaces [14], Polynomial Chaos [15], Kriging [16,17], Neural Network [18], and Support Vector Machine [19,20], etc.”