Kriging-based Response Surfaces

Kriging-Based Response Surfaces is a response surface modeling technique that employs Kriging interpolation—a geostatistical method rooted in Gaussian process regression—to construct surrogate models capable of capturing complex, non-linear relationships between input variables and response outputs while explicitly accounting for spatial correlation among data points.

117

Publications

8.2K

Citations

286

Authors

137

Institutions

Publications per year

2017–2026

31

Variants

Kriging-based Response Surface Methodology

Authors

286

  1. MI
    Marianthi Ierapetritou

    Rutgers, The State University of New Jersey, United States

    5 publications · 287 citations

    5

    h-index

  2. TW
    Timothy W. Simpson

    Pennsylvania State University, United States

    5 publications · 1.8K citations

    5

    h-index

  3. ED
    Eddie Davis

    Rutgers, The State University of New Jersey, United States

    4 publications · 194 citations

    4

    h-index

  4. SO
    Shigeru Obayashi

    Tohoku University, Japan

    3 publications · 56 citations

    3

    h-index

  5. XC
    Xi Chen

    Virginia Tech, United States

    3 publications · 133 citations

    3

    h-index

1–5 of 286

Venues

  1. AIAA Journal

    5 publications · 1.6K citations

    5

    h-index

  2. Structural and Multidisciplinary Optimization

    4 publications · 297 citations

    4

    h-index

  3. European Journal of Operational Research

    3 publications · 195 citations

    3

    h-index

  4. AIChE Journal

    2 publications · 126 citations

    2

    h-index

  5. Journal of Global Optimization

    2 publications · 214 citations

    2

    h-index

1–5