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Prediction of tide level based on variable weight combination of LightGBM and CNN-BiGRU model
Accurate tide level prediction is crucial to human activities in coastal areas. Many practical applications show that compared with traditional harmonic analysis, long short-term memory (LSTM), gated recurrent units (GRUs) and other neural networks, along with ensemble learning models, such as light...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9807633/ https://www.ncbi.nlm.nih.gov/pubmed/36593233 http://dx.doi.org/10.1038/s41598-022-26213-y |