APA (7th ed.) Citation

Nafouanti, M. B., Li, J., Chakira, H., Nyakilla, E. E., Fabiani, D. C., Gondwe, J. F., & Sallah, I. (2025). Prediction of Groundwater Level and its Correlation with Land Subsidence and Groundwater Quality in Cangzhou, North China Plain, Using Time-Series Long Short-Term Memory Neural Network and Hybrid Models. Natural resources research (New York, N.Y.), 34(3), 1645-1666. https://doi.org/10.1007/s11053-025-10474-1

Chicago Style (17th ed.) Citation

Nafouanti, Mouigni Baraka, Junxia Li, Hamada Chakira, Edwin E. Nyakilla, Denice Cleophace Fabiani, Jane Ferah Gondwe, and Ismaila Sallah. "Prediction of Groundwater Level and Its Correlation with Land Subsidence and Groundwater Quality in Cangzhou, North China Plain, Using Time-Series Long Short-Term Memory Neural Network and Hybrid Models." Natural Resources Research (New York, N.Y.) 34, no. 3 (2025): 1645-1666. https://doi.org/10.1007/s11053-025-10474-1.

MLA (9th ed.) Citation

Nafouanti, Mouigni Baraka, et al. "Prediction of Groundwater Level and Its Correlation with Land Subsidence and Groundwater Quality in Cangzhou, North China Plain, Using Time-Series Long Short-Term Memory Neural Network and Hybrid Models." Natural Resources Research (New York, N.Y.), vol. 34, no. 3, 2025, pp. 1645-1666, https://doi.org/10.1007/s11053-025-10474-1.