Galerkin Approximation

Galerkin Approximation is a numerical method in the broader class of projection methods for solving differential equations, distinguished by its use of weighted residuals orthogonal to a finite-dimensional subspace of the solution space to approximate weak solutions.

3.2K

Publications

156.9K

Citations

5.2K

Authors

1.6K

Institutions

Publications per year

2017–2026

654

Variants

Galerkin Method

Publications

3.2K

Authors

5.2K

  1. CS
    Chi‐Wang Shu

    Brown University, United States

    51 publications · 5.4K citations

    36

    h-index

  2. YC
    Yumin Cheng

    Shanghai University, China

    25 publications · 1.6K citations

    24

    h-index

  3. MD
    Mehdi Dehghan

    Amirkabir University of Technology, Iran

    23 publications · 1K citations

    21

    h-index

  4. XL
    Xiaolin Li

    Chongqing Normal University, China

    20 publications · 1K citations

    19

    h-index

  5. BC
    Bernardo Cockburn

    University of Minnesota, United States

    19 publications · 4K citations

    18

    h-index

1–5 of 5.2K

Venues

  1. SIAM Journal on Numerical Analysis

    192 publications · 18.2K citations

    66

    h-index

  2. Journal of Computational Physics

    178 publications · 10.3K citations

    56

    h-index

  3. 51

    h-index

  4. Mathematics of Computation

    MCOM · 118 publications · 9.7K citations

    50

    h-index

  5. 41

    h-index

1–5