Optimal data pooling from multiple waterbodies to improve machine-learning predictions of cyanobacterial blooms.

Accurate early warning of cyanobacterial blooms (CBs) is essential for protecting water resources and public health. However, most monitoring sites provide only small weekly datasets that limit machine-learning (ML) model generalization. Pooling data…

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