Multi-objective Model Optimization

Multi-Objective Model Optimization is a computational framework in hydrological modeling that simultaneously optimizes multiple conflicting objective functions—such as predictive accuracy, model simplicity, and computational efficiency—within the calibration of streamflow prediction models to identify Pareto-optimal solutions.

912

Publications

37.5K

Citations

3K

Authors

1K

Institutions

Publications per year

2017–2026

565

Authors

3K

  1. OG
    Orazio Giustolisi

    Polytechnic University of Bari, Italy

    5 publications · 480 citations

    5

    h-index

  2. JW
    Jichun Wu

    Nanjing University, China

    5 publications · 147 citations

    5

    h-index

  3. AA
    Abbas Afshar

    Iran University of Science and Technology, Iran

    5 publications · 144 citations

    5

    h-index

  4. KC
    Kwok‐wing Chau

    Hong Kong Polytechnic University, Hong Kong SAR China

    5 publications · 846 citations

    5

    h-index

  5. MR
    Mohammad Reza Nikoo

    Shiraz University, Iran

    5 publications · 158 citations

    5

    h-index

1–5 of 3K

Venues

  1. Journal of Hydrology

    43 publications · 3.7K citations

    29

    h-index

  2. Water Resources Research

    27 publications · 2K citations

    24

    h-index

  3. Journal of Cleaner Production

    22 publications · 1.4K citations

    19

    h-index

  4. Water Resources Management

    20 publications · 674 citations

    18

    h-index

  5. Sustainability

    29 publications · 671 citations

    17

    h-index

1–5