Davood Shahsavani

Civil and Structural Engineering · 2010–2015

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Civil and Structural Engineering — 12 citations into it
• Statistics and Probability — 9 citations into it; #3,471 of 12,932 by trust here, #6,080 by citations
• Computational Theory and Mathematics — 6 citations into it; #2,759 of 12,182 by trust here, #5,724 by citations
• Environmental Engineering — 6 citations into it

Whom Davood Shahsavani trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Andrea Saltelli
2. Daniel Busby
3. Jeremy E. Oakley
4. Genyuan Li
5. Anthony OʼHagan
6. Bruno Sudret
7. Jerome H. Friedman
8. Herschel A. Rabitz

Who trusts Davood Shahsavani overall

1. Jon Herman
2. Francesca Campolongo
3. Wei Gong
4. Sergei S. Kucherenko
5. S. Burhenne
6. Qingyun Duan
7. Andrea Saltelli
8. Chen Wang
9. Paul Lemaître
10. Jianduo Li

Papers from Davood Shahsavani's perspective

Ordered by how strongly the researchers Davood Shahsavani trusts endorse each paper. Same corpus, a different order for every researcher.

1. Probabilistic sensitivity analysis of complex models: a Bayesian approach
2. Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models (Reliability Engineering & System Safety)
3. Global sensitivity analysis using polynomial chaos expansions (Reliability Engineering & System Safety)
4. Making best use of model evaluations to compute sensitivity indices
5. Practical Approaches To Construct RS-HDMR Component Functions
6. Book Review: Experiments: Planning, Analysis, and Parameter Design Optimization. By C. F. Jeff Wu and Michael Hamada. John Wiley & Sons, Inc., New York, 2000, 630 p., U.S.$89.95 (hb), ISBN…
7. Hierarchical adaptive experimental design for Gaussian process emulators
8. Quasi-Monte Carlo methods
9. Random number generation and Quasi-Monte Carlo methods
10. Sensitivity Analysis for Nonlinear Mathematical Models. Numerical ExperienceSensitivity Analysis for Nonlinear Mathematical Models. Numerical Experience

Their papers

• Variance-based sensitivity analysis of model outputs using surrogate models (2011) — 370 citations
• Evaluation of MARS modeling technique for sensitivity analysis of model output (2010) — 20 citations
• Estimation of soil cation exchange capacity using Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS) (2015) — 131 citations