191 citations as recorded by crossref.

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53. A state-of-the-art review of long short-term memory models with applications in hydrology and water resources Z. Feng et al. 10.1016/j.asoc.2024.112352
54. Online force prediction by neural networks in single point incremental hole flanging operations L. Besong et al. 10.1007/s10845-024-02512-1
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58. Forecasting of groundwater level variation under changing climate in Chhattisgarh state using deep learning technique M. Dey & C. Singh 10.2166/nh.2025.003
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61. Recurrent neural networks for rainfall-runoff modeling of small Amazon catchments L. de Mendonça et al. 10.1007/s40808-022-01626-w
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66. A critical review on groundwater level depletion monitoring based on GIS and data-driven models: Global perspectives and future challenges M. Monir et al. 10.1016/j.hydres.2024.05.001
67. Multiscale groundwater level forecasts with multi-model ensemble approaches: Combining machine learning models using decision theories and bayesian model averaging D. Roy et al. 10.1016/j.gsd.2024.101347
68. Entity aware sequence to sequence learning using LSTMs for estimation of groundwater contamination release history and transport parameters A. Anshuman & T. Eldho 10.1016/j.jhydrol.2022.127662
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73. Deep learning insights into suspended sediment concentrations across the conterminous United States: Strengths and limitations Y. Song et al. 10.1016/j.jhydrol.2024.131573
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76. Lake Level Evolution of the Largest Freshwater Lake on the Mediterranean Islands through Drought Analysis and Machine Learning Ž. Brkić & M. Kuhta 10.3390/su141610447
77. Bayesian Optimization Algorithm-Based Statistical and Machine Learning Approaches for Forecasting Short-Term Electricity Demand N. Sultana et al. 10.3390/en15093425
78. Forecasting indoor air quality in high-risk operating theatres in hospitals using Artificial Neural Networks A. Rivero-Cacho et al. 10.1016/j.jobe.2025.113339
79. Forecasting organic waste and biomethane generation potential of a non industrial district of Eastern India: A data-driven approach to sustainable energy and waste management A. Ghosh et al. 10.1016/j.clwas.2025.100378
80. Artificial neural network-based model predictive control for optimal operating conditions in proton exchange membrane fuel cells Y. Cho et al. 10.1016/j.jclepro.2022.135049
81. A parallel workflow framework using encoder-decoder LSTMs for uncertainty quantification in contaminant source identification in groundwater A. Anshuman & T. Eldho 10.1016/j.jhydrol.2023.129296
82. A groundwater level spatiotemporal prediction model based on graph convolutional networks with a long short-term memory L. Wang et al. 10.2166/hydro.2024.226
83. Deep transfer learning for groundwater flow in heterogeneous aquifers using a simple analytical model J. Zhang et al. 10.1016/j.jhydrol.2023.130293
84. Safety management system of new energy vehicle power battery based on improved LSTM K. Zhao & H. Bai 10.1186/s42162-024-00411-6
85. Towards a better consideration of rainfall and hydrological spatial features by a deep neural network model to improve flash floods forecasting: case study on the Gardon basin, France B. Saint-Fleur et al. 10.1007/s40808-022-01650-w
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88. Improving the Accuracy of Groundwater Level Forecasting by Coupling Ensemble Machine Learning Model and Coronavirus Herd Immunity Optimizer A. Saqr et al. 10.1007/s11269-025-04210-w
89. A differentiable, physics-informed ecosystem modeling and learning framework for large-scale inverse problems: demonstration with photosynthesis simulations D. Aboelyazeed et al. 10.5194/bg-20-2671-2023
90. Identification of Time-Varying Conceptual Hydrological Model Parameters with Differentiable Parameter Learning X. Lian et al. 10.3390/w16060896
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