Abstract:The rapid advancement in computer technology has supported flood forecasting, especially neural networks (NN), an application of data -driven models. However, predict ion reliability is compromised due to the data manipulation strategies and the length of the predictive horizon, especially the one-month horizon, which is ample for pre-flood management. Therefore, six (06) variants of recurrent neural networks (RNN) such as Long-and Short-Term Model (LSTM ), Gated Recurrent Unit (GRU), Stacked Bidirect ional an… Show more
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