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About this paper
Fearghal O'Donncha, Nikos Papandroulakis, Jennie Korus, Abigail Langbridge, Alexander Timms, Konstantinos Topouzelis, Abdul Baseer Khan, Shree Rama Kamal Kumar Vegu and 5 more
The chapter surveys machine learning for aquaculture, focusing on salmon-farm dissolved oxygen forecasts and satellite-based estimates. A Temporal Fusion Transformer uses cage-level oxygen, temperature, salinity, and time features to predict 24-hour conditions with quantile ranges. Preliminary forecasts had mean absolute error below 0.7 mg/L within one region, but error increased across regions; satellite estimates remained indirect.
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