A team led by Virginia Tech graduate student Samuel Daramola developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, to offer a faster, low-cost tool for flood forecasting.
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