Surrogate-based Sensitivity Analysis

Surrogate-Based Sensitivity Analysis is a systematic method for quantifying the influence of input variables on the output of a computational model by leveraging a surrogate model to approximate the model's behavior and efficiently compute sensitivity indices.

87

Publications

3.7K

Citations

231

Authors

125

Institutions

Publications per year

2017–2026

39

Authors

231

  1. MI
    Marianthi Ierapetritou

    Rutgers, The State University of New Jersey, United States

    4 publications · 174 citations

    4

    h-index

  2. TE
    Thore Egeland

    University of Oslo, Norway

    2 publications · 73 citations

    2

    h-index

  3. DS
    Davood Shahsavani

    University of Shahrood, Iran

    2 publications · 75 citations

    2

    h-index

  4. PS
    Pengjian Shang

    Beijing Jiaotong University, China

    2 publications · 61 citations

    2

    h-index

  5. AR
    Amanda Rogers

    Rutgers, The State University of New Jersey, United States

    2 publications · 124 citations

    2

    h-index

1–5 of 231

Venues

  1. Reliability Engineering & System Safety

    5 publications · 160 citations

    6

    h-index

  2. Applied Mathematical Modelling

    2 publications · 66 citations

    3

    h-index

  3. Chemical Engineering Science

    2 publications · 124 citations

    2

    h-index

  4. AIAA Journal

    2 publications · 125 citations

    2

    h-index

  5. 2

    h-index

1–5