Department Of Computer Science And Information Engineering 1

1. Explainable deep learning hybrid models for enhanced prediction of river dissolved oxygen concentration
2. Hybrid attention based deep learning for forecasting boundary layer ozone using satellite derived profiles
3. Integrating the pressure-state-response model with the extension catastrophe progression for flood risk and resilience assessment
4. Hybrid machine learning and deep learning models for river suspended sediment load forecasting
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