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Material Type: Artigo
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Groundwater level forecasting with artificial neural networks: a comparison of long short-term memory (LSTM), convolutional neural networks (CNNs), and non-linear autoregressive networks with exogenous input (NARX)Wunsch, Andreas ; Liesch, Tanja ; Broda, StefanHydrology and earth system sciences, 2021-04, Vol.25 (3), p.1671-1687 [Periódico revisado por pares]Katlenburg-Lindau: Copernicus GmbHTexto completo disponível |
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Material Type: Artigo
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Spatiotemporal optimization of groundwater monitoring networks using data-driven sparse sensing methodsOhmer, Marc ; Liesch, Tanja ; Wunsch, AndreasHydrology and earth system sciences, 2022-08, Vol.26 (15), p.4033-4053 [Periódico revisado por pares]Katlenburg-Lindau: Copernicus GmbHTexto completo disponível |
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Material Type: Artigo
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Groundwater level forecasting with artificial neural networks: a comparison of long short-term memoryWunsch, Andreas ; Liesch, Tanja ; Broda, StefanHydrology and earth system sciences, 2021-04, Vol.25 (3), p.1671 [Periódico revisado por pares]Copernicus GmbHTexto completo disponível |
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Material Type: Newsletter Articles
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Fraunhofer Institute of Optronics Researchers Describe Findings in Machine LearningJournal of Engineering, 2023, p.784NewsRX LLCTexto completo disponível |
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Material Type: Newsletter Articles
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Findings on Environmental Water Research Reported by Investigators at Karlsruhe Institute of TechnologyEcology, Environment & Conservation, 2021, p.441NewsRX LLCTexto completo disponível |
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Material Type: Newsletter Articles
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Groundwater level threatens to fall in Germany due to climate changeGlobal Warming Focus, 2022, p.183NewsRX LLCTexto completo disponível |