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The Use of Recurrent Neural Networks (S-RNN, LSTM, GRU) For Flood Forecasting Based on Data Extracted from Classical Hydraulic Modeling

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Published in:Modelling in Civil and Environmental Engineering
Format: Online Article RSS Article
Published: 2024
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container_title Modelling in Civil and Environmental Engineering
description
discipline_display Natural Sciences
discipline_facet Natural Sciences
format Online Article
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genre Journal Article
id rss_article:17402
institution FRELIP
journal_source_facet Modelling in Civil and Environmental Engineering
publishDate 2024
publishDateSort 2024
record_format rss_article
spellingShingle The Use of Recurrent Neural Networks (S-RNN, LSTM, GRU) For Flood Forecasting Based on Data Extracted from Classical Hydraulic Modeling
Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
sub_discipline_display Natural Sciences — Mathematical Sciences
sub_discipline_facet Natural Sciences — Mathematical Sciences
subject_display Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
subject_facet Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
title The Use of Recurrent Neural Networks (S-RNN, LSTM, GRU) For Flood Forecasting Based on Data Extracted from Classical Hydraulic Modeling
title_auth The Use of Recurrent Neural Networks (S-RNN, LSTM, GRU) For Flood Forecasting Based on Data Extracted from Classical Hydraulic Modeling
title_full The Use of Recurrent Neural Networks (S-RNN, LSTM, GRU) For Flood Forecasting Based on Data Extracted from Classical Hydraulic Modeling
title_fullStr The Use of Recurrent Neural Networks (S-RNN, LSTM, GRU) For Flood Forecasting Based on Data Extracted from Classical Hydraulic Modeling
title_full_unstemmed The Use of Recurrent Neural Networks (S-RNN, LSTM, GRU) For Flood Forecasting Based on Data Extracted from Classical Hydraulic Modeling
title_short The Use of Recurrent Neural Networks (S-RNN, LSTM, GRU) For Flood Forecasting Based on Data Extracted from Classical Hydraulic Modeling
title_sort the use of recurrent neural networks (s-rnn, lstm, gru) for flood forecasting based on data extracted from classical hydraulic modeling
topic Mathematics
Natural Sciences — Mathematical Sciences
Natural Sciences
url https://sciendo.com/article/10.2478/mmce-2023-0011