Combining autoregressive integrated moving average with Long Short-Term Memory neural network and optimisation algorithms for predicting ground water level

The groundwater resources are the essential sources for irrigation and agriculture management. Forecasting groundwater levels (GWL) for the current and future periods is an essential topic of watershed management. The prediction of GWL helps prevent overexploitation. The Auto-Regressive Integrated M...

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Bibliographic Details
Published in:	Journal of cleaner production Vol. 348; p. 131224
Main Authors:	Sheikh Khozani, Zohreh, Barzegari Banadkooki, Fatemeh, Ehteram, Mohammad, Najah Ahmed, Ali, El-Shafie, Ahmed
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 10.05.2022
Subjects:	algorithms ARIMA models Groundwater hybrids Iran irrigation LSTM models memory neural networks Optimisation prediction statistical models swarms time series analysis water table watershed management Iran Groundwater LSTM models ARIMA models Optimisation
ISSN:	0959-6526, 1879-1786
Online Access:	Get full text
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