Cite
Long short-term memory neural network (LSTM-NN) for aquifer level time series forecasting using in-situ piezometric observations.
MLA
Solgi, Ryan, et al. “Long Short-Term Memory Neural Network (LSTM-NN) for Aquifer Level Time Series Forecasting Using in-Situ Piezometric Observations.” Journal of Hydrology, vol. 601, Oct. 2021, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.jhydrol.2021.126800.
APA
Solgi, R., Loáiciga, H. A., & Kram, M. (2021). Long short-term memory neural network (LSTM-NN) for aquifer level time series forecasting using in-situ piezometric observations. Journal of Hydrology, 601, N.PAG. https://doi.org/10.1016/j.jhydrol.2021.126800
Chicago
Solgi, Ryan, Hugo A. Loáiciga, and Mark Kram. 2021. “Long Short-Term Memory Neural Network (LSTM-NN) for Aquifer Level Time Series Forecasting Using in-Situ Piezometric Observations.” Journal of Hydrology 601 (October): N.PAG. doi:10.1016/j.jhydrol.2021.126800.