Optimization of LSTM Parameters for Flash Flood Forecasting Using Genetic Algorithm
Author:
Funder
National Science and Technology Council
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11269-023-03713-8.pdf
Reference70 articles.
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3. Buslim N, Rahmatullah IL, Setyawan BA, Alamsyah A (2021) Comparing bitcoin's prediction model using GRU, RNN, and LSTM by hyperparameter optimization grid search and random search. Int Conf Cyber IT Serv Manag (CITSM). IEEE, pp 1–6. https://doi.org/10.1109/CITSM52892.2021.9588947
4. Carbune V et al (2020) Fast multi-language LSTM-based online handwriting recognition. Int J Doc Anal Recognit (IJDAR) 23:89–102. https://doi.org/10.1007/s10032-020-00350-4
5. Chang LC, Chang FJ, Wang YP (2009) Auto-configuring radial basis function networks for chaotic time series and flood forecasting. Hydrol Process Int J 23:2450–2459. https://doi.org/10.1002/hyp.7352
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