Development of Long Short-Term Memory Model for Prediction of Water Table Depth in United Arab Emirates-Reference-Cited by-同舟云学术

Development of Long Short-Term Memory Model for Prediction of Water Table Depth in United Arab Emirates

Published:2023 Issue: Volume: Page:141-152
ISSN:0921-092X
Container-title:Water Resources Management and Sustainability
language:
Short-container-title:

Author:

Kumar Pavitra,Ahmed Ali Najah,Sherif Mohsen,Sefelnasr Ahmed,Elshafie Ahmed

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-24506-0_10

Reference21 articles.

1. Abuelgasim A, Elkamali M (2019) Time series analysis of groundwater levels using geographic information systems in Al Ain region, in the United Arab Emirates

2. Afan HA, Ibrahem Ahmed Osman A, Essam Y, Ahmed AN, Huang YF, Kisi O, Sherif M, Sefelnasr A, Chau K, El-Shafie A (2021) Modeling the fluctuations of groundwater level by employing ensemble deep learning techniques. Eng Appl Comput Fluid Mech 15(1):1420–1439. https://doi.org/10.1080/19942060.2021.1974093

3. Al-Ruzouq R, Shanableh A, Merabtene T, Siddique M, Khalil MA, Idris A, Almulla E (2019) Potential groundwater zone mapping based on geo-hydrological considerations and multi-criteria spatial analysis: North UAE. CATENA 173:511–524. https://doi.org/10.1016/j.catena.2018.10.037

4. Chen K (2020) APSO-LSTM: an improved LSTM neural network model based on APSO algorithm. J Phys Conf Ser 1651(1):012151. https://doi.org/10.1088/1742-6596/1651/1/012151

5. Chung H, Shin K (2018) Genetic algorithm-optimized long short-term memory network for stock market prediction. Sustainability 10(10). https://doi.org/10.3390/su10103765

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater;International Journal of Biological Macromolecules;2024-10