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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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2
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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3
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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4
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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5
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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6
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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7
Cluster Forecasting of Corruption Using Nonlinear Autoregressive Models with Exogenous Variables (NARX)—An Artificial Neural Network Analysis
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Cluster Forecasting of Corruption Using Nonlinear Autoregressive Models with Exogenous Variables (NARX)—An Artificial Neural Network Analysis

Ghahari, SeyedAli ; Queiroz, Cesar ; Labi, Samuel ; McNeil, Sue

Sustainability, 2021-10, Vol.13 (20), p.11366 [Peer Reviewed Journal]

Basel: MDPI AG

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8
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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9
Nonlinear autoregressive neural networks with external inputs for forecasting of typhoon inundation level
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Nonlinear autoregressive neural networks with external inputs for forecasting of typhoon inundation level

Ouyang, Huei-Tau

Environmental monitoring and assessment, 2017-08, Vol.189 (8), p.376-376, Article 376 [Peer Reviewed Journal]

Cham: Springer International Publishing

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10
Multistep-ahead forecasting of chlorophyll a using a wavelet nonlinear autoregressive network
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Multistep-ahead forecasting of chlorophyll a using a wavelet nonlinear autoregressive network

Du, Zhenhong ; Qin, Mengjiao ; Zhang, Feng ; Liu, Renyi

Knowledge-based systems, 2018-11, Vol.160, p.61-70 [Peer Reviewed Journal]

Amsterdam: Elsevier B.V

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