Laboratory Data Reconciliation

Laboratory Data Reconciliation is a methodological framework within data reconciliation that specifically integrates and adjusts experimental measurements from laboratory-scale processes to ensure consistency with physical laws, instrument constraints, and thermodynamic models while minimizing measurement uncertainties and systematic errors.

10

Publications

378

Citations

34

Authors

17

Institutions

Publications per year

2017–2026

2

Authors

34

  1. AB
    Ali Behnami

    University of Maragheh, Iran

    1 publications · 15 citations

    1

    h-index

  2. AS
    Alexandre Santuchi da Cunha

    Universidade de São Paulo, Brazil

    1 publications · 29 citations

    1

    h-index

  3. WE
    William E. Cunningham

    University of California, Los Angeles, United States

    1 publications · 15 citations

    1

    h-index

  4. GW
    G.H. Weiss

    The University of Sydney, Australia

    1 publications · 19 citations

    1

    h-index

  5. DB
    Derya B. Özyurt

    Louisiana State University, United States

    1 publications · 211 citations

    1

    h-index

1–5 of 34

Venues

  1. Computers & Chemical Engineering

    4 publications · 273 citations

    4

    h-index

  2. PubMed

    Repository · 1 publications · 17 citations

    1

    h-index

  3. International Journal of Medical Informatics

    1 publications · 15 citations

    1

    h-index

  4. Bioprocess and Biosystems Engineering

    1 publications · 22 citations

    1

    h-index

  5. Annual Reviews in Control

    1 publications · 23 citations

    1

    h-index

1–5