EcologybioRxivPreprint
A Low-Resource Machine-Learning Framework for Cold-Stress Early Warning in Aquaculture Nursery Ponds Using Manual Temperature Readings
Imran Bin Younos, Nushrat Jahan
The paper develops a low-resource machine learning framework using manual temperature readings to predict cold stress in aquaculture ponds, achieving effective early warnings with XGBoost models.
DOI 10.64898/2026.08.01.742243