Global Error Measures

Global Error Measures is a quantitative framework used in numerical analysis and computational mathematics to assess the cumulative deviation between an approximate solution and the exact solution over an entire domain or time interval, distinguishing it from local error measures by integrating errors across all steps or spatial locations.

112

Publications

6K

Citations

302

Authors

165

Institutions

Publications per year

2017–2026

12

Authors

302

  1. GY
    Gennady Yu. Kulikov

    University of Lisbon, Portugal

    8 publications · 195 citations

    8

    h-index

  2. RW
    R. Weiner

    Martin Luther University Halle-Wittenberg, Germany

    4 publications · 105 citations

    4

    h-index

  3. HW
    H.A. Watts

    Sandia National Laboratories California, United States

    2 publications · 99 citations

    2

    h-index

  4. AC
    Alexis Comber

    University of Leeds, United Kingdom

    2 publications · 80 citations

    2

    h-index

  5. SP
    Sundeep Prabhakar Chepuri

    Delft University of Technology, Netherlands

    2 publications · 72 citations

    2

    h-index

1–5 of 302

Venues

  1. 7

    h-index

  2. 7

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  3. IMA Journal of Numerical Analysis

    4 publications · 169 citations

    4

    h-index

  4. ACM Transactions on Mathematical Software

    TOMS · 3 publications · 119 citations

    3

    h-index

  5. 2

    h-index

1–5