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This research aims to enhance flood forecasting accuracy in vulnerable coastal communities using advanced AI techniques.

March 4, 2026Open Access

AI-Powered Community Flood Forecasting in Coastal Senegal: A Methodological Approach

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Hybrid AI model predicts flood events in coastal communities, highlighting the need for better early warning systems.

This research aims to enhance flood forecasting accuracy in vulnerable coastal communities using advanced AI techniques.
Developed a hybrid machine learning model combining recurrent neural networks with Bayesian inference.
Trained the model on historical precipitation data and extreme weather indices.
Utilized uncertainty quantification through likelihood-based methods for confidence interval estimation.
Achieved an 85% accuracy rate in predicting flood events.
Maintained a mean absolute error (MAE) within ±1 day for predicted flood timing.
Demonstrated improved flood warning capabilities beneficial for community response planning.

Samb et al. (2006) studied this question.

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