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

The application of a nonlinear autoregressive modeling approach with exogenous input (NARX) neural networks for modeling groundwater level fluctuation has been examined by several researchers. However, the suitability of NARX in modeling groundwater level dynamics in urbanized and arid aquifer syste...

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Veröffentlicht in:	Water (Basel) 2020-03, Vol.12 (3), p.820
1. Verfasser:	Alsumaiei, Abdullah A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Aquifer systems Aquifers Artificial intelligence Artificial recharge Autoregressive models Comparative analysis Correlation analysis Datasets Desalination Environmental aspects Groundwater Groundwater levels Groundwater recharge Hydrology Irrigation Mathematical models Measurement Methods Neural networks Observation wells Precipitation Researchers Shallow water Statistical analysis Statistical models Studies Surface water Temperature Time series Water management Water shortages Water supply Water table Water, Underground
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