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Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)
Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)
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Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)

Wunsch, Andreas ; Liesch, Tanja ; Broda, Stefan

Journal of hydrology (Amsterdam), 2018-12, Vol.567, p.743-758 [Peer Reviewed Journal]

Elsevier B.V

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Hydrology; New Hydrology Findings from Karlsruhe Institute of Technology Described [Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)]
Hydrology; New Hydrology Findings from Karlsruhe Institute of Technology Described [Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)]
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Hydrology; New Hydrology Findings from Karlsruhe Institute of Technology Described [Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input (NARX)]

Science Letter, 2019, p.661

Atlanta: NewsRx

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3
Groundwater level forecasting in Northern Bangladesh using nonlinear autoregressive exogenous (NARX) and extreme learning machine (ELM) neural networks
Groundwater level forecasting in Northern Bangladesh using nonlinear autoregressive exogenous (NARX) and extreme learning machine (ELM) neural networks
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Groundwater level forecasting in Northern Bangladesh using nonlinear autoregressive exogenous (NARX) and extreme learning machine (ELM) neural networks

Fabio, Di Nunno ; Abba, S. I. ; Pham, Bao Quoc ; Towfiqul Islam, Abu Reza Md ; Talukdar, Swapan ; Francesco, Granata

Arabian journal of geosciences, 2022, Vol.15 (7), Article 647 [Peer Reviewed Journal]

Cham: Springer International Publishing

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4
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)
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)
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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, Stefan

Hydrology and earth system sciences, 2021-04, Vol.25 (3), p.1671-1687 [Peer Reviewed Journal]

Katlenburg-Lindau: Copernicus GmbH

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5
A Nonlinear Autoregressive Modeling Approach for Forecasting Groundwater Level Fluctuation in Urban Aquifers
A Nonlinear Autoregressive Modeling Approach for Forecasting Groundwater Level Fluctuation in Urban Aquifers
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A Nonlinear Autoregressive Modeling Approach for Forecasting Groundwater Level Fluctuation in Urban Aquifers

Alsumaiei, Abdullah A.

Water (Basel), 2020-03, Vol.12 (3), p.820 [Peer Reviewed Journal]

Basel: MDPI AG

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6
New Hydrology Findings from Karlsruhe Institute of Technology Described [Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input ]
New Hydrology Findings from Karlsruhe Institute of Technology Described [Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input ]
Material Type:
Newsletter Articles 		Add to e-Shelf

New Hydrology Findings from Karlsruhe Institute of Technology Described [Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input ]

Science Letter, 2019, p.661

NewsRX LLC

Full text available

Citations Cited by
7
New Hydrology Findings from Karlsruhe Institute of Technology Described [Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input
New Hydrology Findings from Karlsruhe Institute of Technology Described [Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input
Material Type:
Newsletter Articles 		Add to e-Shelf

New Hydrology Findings from Karlsruhe Institute of Technology Described [Forecasting groundwater levels using nonlinear autoregressive networks with exogenous input

Science Letter, 2019, p.661-661

NewsRX LLC

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8
A Water Consumption Forecasting Model by Using a Nonlinear Autoregressive Network with Exogenous Inputs Based on Rough Attributes
A Water Consumption Forecasting Model by Using a Nonlinear Autoregressive Network with Exogenous Inputs Based on Rough Attributes
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A Water Consumption Forecasting Model by Using a Nonlinear Autoregressive Network with Exogenous Inputs Based on Rough Attributes

Zheng, Yihong ; Zhang, Wanjuan ; Xie, Jingjing ; Liu, Qiao

Water (Basel), 2022-02, Vol.14 (3), p.329 [Peer Reviewed Journal]

Basel: MDPI AG

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9
Long-term forecasting system using wavelet – nonlinear autoregressive neural network conjunction model
Long-term forecasting system using wavelet – nonlinear autoregressive neural network conjunction model
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Long-term forecasting system using wavelet – nonlinear autoregressive neural network conjunction model

Kummong, Ratree ; Supratid, Siriporn

Journal of modelling in management, 2019-10, Vol.14 (4), p.948-971 [Peer Reviewed Journal]

Bradford: Emerald Publishing Limited

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10
Short-Term Wind Speed Forecasting Using Nonlinear Autoregressive Neural Network: A Case Study in Kocaeli-Türkiye
Short-Term Wind Speed Forecasting Using Nonlinear Autoregressive Neural Network: A Case Study in Kocaeli-Türkiye
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Short-Term Wind Speed Forecasting Using Nonlinear Autoregressive Neural Network: A Case Study in Kocaeli-Türkiye

Gidom, Maysa ; Kökçam, Abdullah H. ; Uyaroğlu, Yılmaz

Electric power components and systems, 2024-02, Vol.52 (3), p.381-399 [Peer Reviewed Journal]

Philadelphia: Taylor & Francis

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