The findings indicate that artificial neural networks and random forest models were most frequently reported as high performing within individual studies, but direct comparisons across studies are limited by heterogeneity in prediction targets, validation strategies, lead times, heatwave definitions, and performance me...
Adam Ashford, Fahad Ayaz, M. Shakir et al.· Forecasting· 0 citations
The analysis reveals a transition from deterministic DI models to hybrid, physics-informed, uncertainty-aware, and operational forecasting systems that increasingly integrate AI with physical knowledge and heterogeneous environmental observations.
Braiton U. Mukhalela, S. Viriri, D. Ndzi et al.· Frontiers in Artificial Inte...· 0 citations
Flood intensity and frequency are expected to continue rising due to climate change, necessitating improved prevention measures. Despite the growing body of research, communities and economies remain severely affected by the consequences of floods, underscoring the need to examine how flood models are understood and tr...
Irvin D. Shandu, M. Gebreslasie, Sifiso Xulu et al.· Frontiers in Water· 0 citations
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