Decision Rule Optimization

Decision Rule Optimization is a methodological framework within decision-level fusion that systematically refines the criteria for combining disparate classifier outputs to maximize overall decision accuracy and robustness under specific performance constraints.

190

Publications

11.2K

Citations

473

Authors

259

Institutions

Publications per year

2017–2026

35

Authors

473

  1. CR
    Charles ReVelle

    Johns Hopkins University, United States

    6 publications · 534 citations

    6

    h-index

  2. OR
    Oscar R. Burt

    Montana State University, United States

    3 publications · 317 citations

    3

    h-index

  3. HG
    How‐Ran Guo

    National Cheng Kung University, Taiwan

    3 publications · 97 citations

    3

    h-index

  4. CH
    Chien‐Cheng Huang

    Chi Mei Medical Center, Taiwan

    3 publications · 97 citations

    3

    h-index

  5. BZ
    Beata Zielosko

    University of Silesia in Katowice, Poland

    3 publications · 68 citations

    3

    h-index

1–5 of 473

Venues

  1. Management Science

    11 publications · 1.6K citations

    11

    h-index

  2. Water Resources Research

    9 publications · 683 citations

    9

    h-index

  3. 4

    h-index

  4. 4

    h-index

  5. IEEE Transactions on Information Theory

    3 publications · 474 citations

    3

    h-index

1–5