Machine Learning-based Ocean Forecasting

Machine Learning-Based Ocean Forecasting is a computational forecasting approach that employs machine learning algorithms to model and predict oceanic states by learning patterns from observational and numerical data, distinguishing it from traditional physics-based ocean forecasting methods.

127

Publications

6.1K

Citations

487

Authors

213

Institutions

Publications per year

2017–2026

100

Authors

487

  1. FO
    Fearghal O’Donncha

    IBM Research - Ireland, Ireland

    3 publications · 121 citations

    3

    h-index

  2. DM
    Dina Makarynska

    Curtin University, Australia

    3 publications · 239 citations

    3

    h-index

  3. OM
    Oleg Makarynskyy

    University of Tabriz, Iran

    3 publications · 239 citations

    3

    h-index

  4. SJ
    Scott James

    Baylor University, United States

    3 publications · 121 citations

    3

    h-index

  5. YZ
    Yushan Zhang

    University of Notre Dame, United States

    3 publications · 121 citations

    3

    h-index

1–5 of 487

Venues

  1. Ocean Engineering

    9 publications · 329 citations

    9

    h-index

  2. Journal of Marine Science and Engineering

    8 publications · 283 citations

    8

    h-index

  3. IEEE Access

    6 publications · 111 citations

    6

    h-index

  4. Water

    4 publications · 175 citations

    4

    h-index

  5. Remote Sensing

    4 publications · 162 citations

    4

    h-index

1–5