233 citations as recorded by crossref.

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2. Unravelling Groundwater–Precipitation Interactions in Karst Aquifers Under the Dual Pressures of Climate Variability and Human Disturbance L. Huang et al.
3. MONTHLY STREAM FLOWS ESTIMATION IN THE KARASU RIVER OF EUPHRATES BASIN WITH ARTIFICIAL NEURAL NETWORKS APPROACH O. KATİPOĞLU
4. Geospatial Artificial Intelligence (GeoAI) in the Integrated Hydrological and Fluvial Systems Modeling: Review of Current Applications and Trends C. Gonzales-Inca et al.
5. Asynchronous parallel surrogate optimization aided neural network design with variable evaluation runtime for streamflow and pollutant forecast W. Xia et al.
6. Insight into groundwater level prediction with feature effectiveness: comparison of machine learning and numerical methods M. Goodarzi et al.
7. Exploring the Potential of Long Short‐Term Memory Networks for Improving Understanding of Continental‐ and Regional‐Scale Snowpack Dynamics Y. Wang et al.
8. Multi-site deep learning for groundwater level prediction across global datasets: toward scalable applications under data scarcity A. Nolte et al.
9. Applications of Convolutional Neural Network for Classification of Land Cover and Groundwater Potentiality Zones A. Tegegne & G. Angiulli
10. Machine learning for groundwater levels: uncovering the best predictors M. Saleh & H. Rasel
11. Carbon Emission Based Predictions of Anthropogenic Impacts on Groundwater Storage at Typical Basins in 2050 Y. Zhao et al.
12. Hybrid model for daily runoff interval predictions based on Bayesian inference H. Xu et al.
13. Towards a global spatial machine learning model for seasonal groundwater level predictions in Germany S. Kunz et al.
14. Dual‐Branch Spectral‐Trend Attention Network With Gated Flux–Momentum Decomposition for Multiscale Financial Time‐Series Forecasting P. Singh & B. Raman
15. Predicting indoor particle concentration in mechanically ventilated classrooms using neural networks: Model development and generalization ability analysis J. Ren et al.
16. Prediction of Tail Water Level under the Influence of Backwater Effect Based on Deep Learning Models: A Case Study in the Xiangjiaba Hydropower Station S. Zhang et al.
17. Assessment on the thermal efficiency of deep borehole heat exchangers under rock and soil heterogeneity Z. Ba et al.
18. Deep learning for groundwater level simulation in unconfined aquifers across the contiguous United States: Analyzing simulations at multiple lead times and integrating groundwater signatures K. Boo et al.
19. Soft causal constraints in groundwater machine learning: a new way to balance accuracy and physical consistency A. Adombi & R. Chesnaux
20. Convolutional long short-term memory neural network for groundwater change prediction S. Patra & H. Chu
21. Convolutional neural network and long short-term memory models for ice-jam predictions F. Madaeni et al.
22. Constraint relaxation active thermal management strategy under multi-source perturbations to enhance fuel cell vehicle's output power and voltage consistency J. Cao et al.
23. Study on Temporal Convolutional Network Rainfall Prediction Model and Its Interpretability Guided by Physical Mechanisms D. Ma et al.
24. Application of a Hybrid CNN-LSTM Model for Groundwater Level Forecasting in Arid Regions: A Case Study from the Tailan River Basin S. Hu et al.
25. A novel operational water quality mobile prediction system with LSTM-Seq2Seq model L. Xie et al.
26. Electric Vehicle Battery State of Charge Estimation With an Ensemble Algorithm Using Central Difference Kalman Filter (CDKF) and Non-Linear Autoregressive With Exogenous Input (NARX) A. Ogundana et al.
27. Prediction of groundwater levels using a long short-term memory (LSTM) technique A. Thakur et al.
28. Karst spring discharge modeling based on deep learning using spatially distributed input data A. Wunsch et al.
29. Interannual and seasonal variations of permafrost thaw depth on the Qinghai-Tibetan Plateau: A comparative study using long short-term memory, convolutional neural networks, and random forest Q. Liu et al.
30. Forecasting of water quality parameters of Sandia station in Narmada basin, Central India, using AI techniques D. Tiwari et al.
31. Long short‐term memory model for predicting groundwater level in Alabama V. Robinson et al.
32. Comparison of artificial neural networks and reservoir models for simulating karst spring discharge on five test sites in the Alpine and Mediterranean regions G. Cinkus et al.
33. Pollution source apportionment and application of machine learning approaches in surface water suitability for irrigation based on hydro chemical analysis A. Das
34. A Novel Fused NARX-Driven Digital Twin Model for Aeroengine Gas Path Parameter Prediction C. Xu et al.
35. Runoff projection in the Tibetan Plateau using a long short-term memory network-based framework under various climate scenarios H. Chu et al.
36. Machine learning for postprocessing ensemble streamflow forecasts S. Sharma et al.
37. Modeling Water Table Response in Apulia (Southern Italy) with Global and Local LSTM-Based Groundwater Forecasting L. Di Taranto et al.
38. A review of machine learning approaches for improving calibration and performance of low-cost air quality sensor networks C. Yan
39. Drone motion prediction from flight data: a nonlinear time series approach S. Dong et al.
40. A process-driven deep learning hydrological model for daily rainfall-runoff simulation H. Li et al.
41. Application of Nonlinear Time Series and Machine Learning Algorithms for Forecasting Groundwater Flooding in a Lowland Karst Area B. Basu et al.
42. Data‐Driven Estimation of Groundwater Level Time‐Series at Unmonitored Sites Using Comparative Regional Analysis E. Haaf et al.
43. Groundwater Level Prediction and Earthquake Precursor Anomaly Analysis Based on TCN-LSTM-Attention Network X. Chen et al.
44. Multiorder hydrologic Position for Europe — a Set of Features for Machine Learning and Analysis in Hydrology M. Nölscher et al.
45. Future projection of water resources based on digitalisation and open data in a water-rich region: a case study of the city of Klagenfurt M. Oberascher et al.
46. Sustainable groundwater management using stacked LSTM with deep neural network E. Alabdulkreem et al.
47. Evaluation of streamflow predictions from LSTM models in water- and energy-limited regions in the United States K. Khand & G. Senay
48. A novel hybrid model by integrating TCN with TVFEMD and permutation entropy for monthly non-stationary runoff prediction H. Wang et al.
49. Multi-head attention driven aggregation-differentiation network for probabilistic groundwater depth forecasting and depth-stratified early warning: A multi-site efficient framework J. Xu et al.
50. Groundwater level forecasting with machine learning models: A review K. Boo et al.
51. A Stepwise Clustered Hydrological Model for Addressing the Temporal Autocorrelation of Daily Streamflows in Irrigated Watersheds K. Li et al.
52. Drug Design and Disease Diagnosis: The Potential of Deep Learning Models in Biology S. Sreeraman et al.
53. Soil moisture as a key predictor for regional groundwater levels: a deep learning study from Brandenburg, Germany M. Eckert & A. Rudolph
54. Machine Learning for Surrogate Groundwater Modelling of a Small Carbonate Island K. Payne et al.
55. Development of a Joint Probabilistic Rainfall‐Runoff Model for High‐to‐Extreme Flow Projections Under Changing Climatic Conditions K. Li et al.
56. Integrated probabilistic forecasting framework for long-term reservoir outflow through dynamic coupling of meteorological–hydrological–engineering processes J. Tan et al.
57. Overcoming hydrological forecasting challenges through augmented adaptive deep algorithms: a case study of the great lakes across Canada and the U.S M. Zeynoddin et al.
58. Deep learning framework with Bayesian data imputation for modelling and forecasting groundwater levels E. Chen et al.
59. Technical note: Data assimilation and autoregression for using near-real-time streamflow observations in long short-term memory networks G. Nearing et al.
60. Hybrid support vector regression models with algorithm of innovative gunner for the simulation of groundwater level T. Roshni et al.
61. Balancing prediction accuracy and model complexity in groundwater forecasting: a multi-objective LSTM framework for urban aquifers A. Alsumaiei
62. Data-driven modelling of hydraulic-head time series: results and lessons learned from the 2022 Groundwater Time Series Modelling Challenge R. Collenteur et al.
63. Ensemble deep learning framework for groundwater storage forecasting under hydrological variability A. Dandapat et al.
64. Fog-Enabled Machine Learning Approaches for Weather Prediction in IoT Systems: A Case Study B. İşler et al.
65. Applications of Physics-Informed Neural Networks in Groundwater Science: Hydraulic Parameter Estimation and Groundwater-level Monitoring Data Quality Management H. Lee et al.
66. Estimating groundwater depth in a coastal drained field using a process- and data-driven hybrid model Y. XU et al.
67. A causal physics-informed deep learning formulation for groundwater flow modeling and climate change effect analysis A. Adombi et al.
68. A Comparative Analysis of Multiple Machine Learning Methods for Flood Routing in the Yangtze River L. Zhou & L. Kang
69. Groundwater level prediction with meteorologically sensitive Gated Recurrent Unit (GRU) neural networks A. Gharehbaghi et al.
70. A state-of-the-art review of long short-term memory models with applications in hydrology and water resources Z. Feng et al.
71. Online force prediction by neural networks in single point incremental hole flanging operations L. Besong et al.
72. From unreliable observations to reliable forecasts: Enhancing Jakarta flood prediction using HEC-HMS-assisted LSTM modeling H. Kardhana et al.
73. Groundwater level prediction in urban karst regions: The comparison of ensemble learning and deep learning models by considering climate conditions X. Song et al.
74. Evaluation and optimization of the water diversion system of ecohydrological restoration megaproject of Tarim River, China, through wavelet analysis and a neural network Q. Liu et al.
75. Wavelet gated multiformer for groundwater time series forecasting V. Serravalle Reis Rodrigues et al.
76. Towards understanding the influence of seasons on low-groundwater periods based on explainable machine learning A. Wunsch et al.
77. Forecasting of groundwater level variation under changing climate in Chhattisgarh state using deep learning technique M. Dey & C. Singh
78. Groundwater science in the age of AI: emerging paradigms and challenges M. Rahman et al.
79. AAF-Bi-LSTM-NARX: A bidirectional network with adaptive attention fusion for sensor data imputation Z. Zhao et al.
80. Using liquid time-constant neural networks combined with water balance equations for groundwater level prediction in karst aquifers Y. Wang et al.
81. Exploring different representations of hydraulic tomographic data for deep learning: Sequence or image Y. Ji et al.
82. Differential Diagnosis of Urinary Cancers by Surface-Enhanced Raman Spectroscopy and Machine Learning L. Song et al.
83. Recurrent neural networks for rainfall-runoff modeling of small Amazon catchments L. de Mendonça et al.
84. Integrating physics-based constraints with gated recurrent unit for improved groundwater level fluctuation prediction J. Jeong et al.
85. Assessment of groundwater variability using ARIMA, random forest, and LSTM-RNN in the northeastern region of Bangladesh A. Nury et al.
86. Improving Long-Term Flood Forecasting Accuracy Using Ensemble Deep Learning Models and an Attention Mechanism M. Kordani et al.
87. Using Artificial Intelligence Algorithms to Estimate and Short-Term Forecast the Daily Reference Evapotranspiration with Limited Meteorological Variables S. Fang et al.
88. Groundwater depth prediction based on CNN-GRU-attention model H. Wei et al.
89. A critical review on groundwater level depletion monitoring based on GIS and data-driven models: Global perspectives and future challenges M. Monir et al.
90. Multiscale groundwater level forecasts with multi-model ensemble approaches: Combining machine learning models using decision theories and bayesian model averaging D. Roy et al.
91. Entity aware sequence to sequence learning using LSTMs for estimation of groundwater contamination release history and transport parameters A. Anshuman & T. Eldho
92. Modeling the Dynamics of the Jebel Zaghouan Karst Aquifer Using Artificial Neural Networks: Toward Improved Management of Vulnerable Water Resources E. Gargouri-Ellouze et al.
93. A parsimonious methodological framework for short-term forecasting of groundwater levels A. Collados-Lara et al.
94. A Comparison of Ensemble and Deep Learning Algorithms to Model Groundwater Levels in a Data-Scarce Aquifer of Southern Africa Z. Gaffoor et al.
95. Impact of Future Climate Change on Groundwater Storage in China’s Large Granary: A Study Based on LSTM and CMIP6 Models H. Wang et al.
96. Prediction of surface urban heat island based on predicted consequences of urban sprawl using deep learning: A way forward for a sustainable environment S. Fu et al.
97. Deep learning insights into suspended sediment concentrations across the conterminous United States: Strengths and limitations Y. Song et al.
98. Application of Hybrid Machine Learning for Groundwater Level Prediction: A Comprehensive Review C. Biswakalyani et al.
99. Hybrid machine learning for predicting groundwater level: A comparison of boosting algorithms with neural networks M. Barzegar et al.
100. Modeling of daily groundwater level using deep learning neural networks M. OTHMAN
101. Lake Level Evolution of the Largest Freshwater Lake on the Mediterranean Islands through Drought Analysis and Machine Learning Ž. Brkić & M. Kuhta
102. Bayesian Optimization Algorithm-Based Statistical and Machine Learning Approaches for Forecasting Short-Term Electricity Demand N. Sultana et al.
103. Forecasting indoor air quality in high-risk operating theatres in hospitals using Artificial Neural Networks A. Rivero-Cacho et al.
104. Spatiotemporal prediction and attribution of groundwater storage anomaly using enhanced hybrid deep learning modeling with uncertainty quantification J. Yin et al.
105. 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.
106. Artificial neural network-based model predictive control for optimal operating conditions in proton exchange membrane fuel cells Y. Cho et al.
107. A parallel workflow framework using encoder-decoder LSTMs for uncertainty quantification in contaminant source identification in groundwater A. Anshuman & T. Eldho
108. A groundwater level spatiotemporal prediction model based on graph convolutional networks with a long short-term memory L. Wang et al.
109. Hybrid modeling for daily streamflow forecasting: A study over the contiguous United States F. Zeng et al.
110. Deep transfer learning for groundwater flow in heterogeneous aquifers using a simple analytical model J. Zhang et al.
111. Interpretable deep learning for sewer network water level forecasting in a Northern Chinese City: Implications for enhancing real-time assessment of system operational conditions Z. Yi et al.
112. Validation strategies for deep learning-based groundwater level time series prediction using exogenous meteorological input features F. Doll et al.
113. Safety management system of new energy vehicle power battery based on improved LSTM K. Zhao & H. Bai
114. Modification and Recalibration of an Existing Groundwater Model of Shelby County, Tennessee K. Hasan et al.
115. 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.
116. Groundwater level forecasting using ensemble coactive neuro-fuzzy inference system K. Boo et al.
117. Explainable and Reduced-Feature Machine learning models for shape and drag prediction of a freely moving drop in the sub-critical Weber number regime M. Tonmoy et al.
118. Improving the Accuracy of Groundwater Level Forecasting by Coupling Ensemble Machine Learning Model and Coronavirus Herd Immunity Optimizer A. Saqr et al.
119. A differentiable, physics-informed ecosystem modeling and learning framework for large-scale inverse problems: demonstration with photosynthesis simulations D. Aboelyazeed et al.
120. Identification of Time-Varying Conceptual Hydrological Model Parameters with Differentiable Parameter Learning X. Lian et al.
121. Balancing accuracy and efficiency in multi-step building-level electric load forecasting: Deep learning vs. classical time-series models N. Sultana
122. Disturbance Estimator-Based Deep Distributed MPC for Satellite CEACS S. Aslam et al.
123. Streamflow Simulation Using a Hybrid Approach Combining HEC-HMS and LSTM Model in the Tlawng River Basin of Mizoram, India S. Debbarma et al.
124. On the challenges of global entity-aware deep learning models for groundwater level prediction B. Heudorfer et al.
125. Reservoir outflow prediction using adaptive neuro-fuzzy interference system A. Tatavarthi et al.
126. A coupled spatial reduction-reconstruction and LSTM framework (SRR-LSTM) for groundwater level prediction in large irrigation districts H. Wei et al.
127. Optimized Intelligent Auto-Regressive Neural Network Model (ARNN) for Prediction of Non-Linear Exogenous Signals L. Farhi & A. Yasir
128. High-frequency data significantly enhances the prediction ability of point and interval estimation X. Liu et al.
129. Groundwater level forecasting in response to climate change scenarios in southwestern Saskatchewan using wavelet decomposition and artificial neural networks A. Okasha et al.
130. Long-term drought effects on landscape water storage and recovery under contrasting landuses S. Luo et al.
131. Analyzing natural gas price projections with innovative hybrid modeling Z. Zhao
132. Machine Learning-Based Water Management Strategies for Sustainable Groundwater Resources S. Sanu & M. Math
133. Advanced groundwater level forecasting with hybrid deep learning model: Tackling water challenges in Taiwan’s largest alluvial fan Y. Chang et al.
134. Research on parameter identification and fault prediction method of hydraulic system in intelligent sensing agriculture W. Liu et al.
135. Predicting Groundwater Level Based on Machine Learning: A Case Study of the Hebei Plain Z. Wu et al.
136. Hybrid Feature Selection Approach to Finding Optimal Feature Subsets for Vehicle Lateral Velocity Estimation G. Hwang et al.
137. The Applications of Soft Computing Methods for Seepage Modeling: A Review V. Nourani et al.
138. Interaction Modeling of Surface Water and Groundwater: An Evaluation of Current and Future Issues N. Khurshid et al.
139. A new method for predicting chlorophyll-a concentration in a reservoir: Coupling EFDC hydrodynamic and water quality model with ConvLSTM-MLP network H. Meng et al.
140. Groundwater quality prediction using novel hybrid classification and regression models M. Nafouanti et al.
141. Sediment load prediction in Johor river: deep learning versus machine learning models S. Latif et al.
142. Investigating the role of ENSO in groundwater temporal variability across Abu Dhabi Emirate, United Arab Emirates using machine learning algorithms K. Alghafli et al.
143. Prediction of the Irrigation Area Carrying Capacity in the Tarim River Basin under Climate Change Q. Liu et al.
144. An AHP based approach to forecast groundwater level at potential recharge zones of Uckermark District, Brandenburg, Germany A. Raihan et al.
145. Deep dive into predictive excellence: Transformer's impact on groundwater level prediction W. Sun et al.
146. Direct impact of climate change on groundwater levels in the Iberian Peninsula A. Rouhani et al.
147. Incorporating dynamic drainage supervision into deep learning for accurate real-time flood simulation in urban areas H. Ren et al.
148. Machine Learning-Based Reconstruction and Prediction of Groundwater Time Series in the Allertal, Germany T. Tran et al.
149. A downscaling-calibrating framework for generating gridded daily precipitation estimates with a high spatial resolution J. Gu et al.
150. Simulation of regional groundwater levels in arid regions using interpretable machine learning models Q. Liu et al.
151. Explainable deep learning-based simulation for evaluating climate-driven future groundwater level changes in South Korea J. Hwang & K. Lee
152. Enhancing process-based hydrological models with embedded neural networks: A hybrid approach B. Li et al.
153. Simulation of Quantity and Quality of Saq Aquifer Using Artificial Intelligence and Hydraulic Models A. Ghumman et al.
154. Optimizing coastal groundwater quality predictions: A novel data mining framework with cross-validation, bootstrapping, and entropy analysis A. Islam et al.
155. AutoML-GWL: Automated machine learning model for the prediction of groundwater level A. Singh et al.
156. Climate driven generative time-varying model for improved decadal storm power predictions in the Mediterranean N. Diodato et al.
157. Model-based prediction of water levels for the Great Lakes: a comparative analysis O. Kurt
158. High Resolution Water Table Modeling of the Shallow Groundwater Using a Knowledge-Guided Gradient Boosting Decision Tree Model J. Koch et al.
159. Groundwater level prediction using machine learning models: A comprehensive review H. Tao et al.
160. Using Simple LSTM Models to Evaluate Effects of a River Restoration on Groundwater in Kushiro Wetland, Hokkaido, Japan T. Yamaguchi et al.
161. Application of the Data-Driven Method and Hydrochemistry Analysis to Predict Groundwater Level Change Induced by the Mining Activities: A Case Study of Yili Coalfield in Xinjiang, Norwest China A. Luo et al.
162. Implementing Recurrent Neural Networks in Process Systems Engineering applications, the right way! A. Chandrasekar et al.
163. Trends, challenges, and opportunities in groundwater level modeling with machine learning M. Hou et al.
164. Multi-step-ahead prediction of river flow using NARX neural networks and deep learning LSTM G. Hayder et al.
165. A multi-layer nesting and integration approach for predicting groundwater levels in agriculturally intensive areas using data-driven models F. Zhu et al.
166. Shallow vs. Deep Learning Models for Groundwater Level Prediction: A Multi-Piezometer Data Integration Approach A. Yeganeh et al.
167. Characteristics and Prediction of Reservoir Water Quality under the Rainfall-Runoff Impact by Long Short-Term Memory Based Encoder-Decoder Model X. Sheng et al.
168. A SOM-LSTM combined model for groundwater level prediction in karst critical zone aquifers considering connectivity characteristics F. Guo et al.
169. Analysis and prediction of groundwater salinity on Yongxing Island using multiple machine learning models integrated with sparrow search algorithm C. Xia et al.
170. Prediction of nitrate concentration and the impact of land use types on groundwater in the Nansi Lake Basin J. Iqbal et al.
171. Basin-wide groundwater-level forecasting in Kumamoto, Japan: integrating transfer learning with long short-term memory network A. Rahman et al.
172. Enhancement groundwater level prediction using hybrid ANN-HHO model: case study (Shabestar Plain in Iran) E. Mirzania et al.
173. Graph neural network for groundwater level forecasting T. Bai & P. Tahmasebi
174. Research on Climate Drivers of Ecosystem Services’ Value Loss Offset in the Qinghai–Tibet Plateau Based on Explainable Deep Learning W. Liu et al.
175. Time Distributed Deep Learning Models for Purely Exogenous Forecasting: Application to Water Table Depth Predictions Using Weather Image Time Series M. Salis et al.
176. Forecasting groundwater level of karst aquifer in a large mining area using partial mutual information and NARX hybrid model W. Zhang et al.
177. Dimensionality reduction for groundwater forecasting under drought and intensive irrigation with neural networks T. Bouramtane et al.
178. Updated multi-layer perceptron algorithm for predicting solute transport parameters and processes in karst conduits with variable flow rates X. Zhao et al.
179. A transformer neural network for predicting near‐surface temperature E. Alerskans et al.
180. GEMS-GER: a machine learning benchmark dataset of long-term groundwater levels in Germany with meteorological forcings and site-specific environmental features M. Ohmer et al.
181. A comparative analysis of machine and deep learning models for predictive maintenance and fault estimation of tools in industrial machinery within small-scale settings Y. Öztürk
182. KI-Modellierung für das Quellmanagement: Vorhersage von Karstquellschüttung und Wasserqualität mittels interpretierbarer Machine-Learning-Modelle A. Pölz et al.
183. Modeling a Practical Dual-Fuel Gas Turbine Power Generation System Using Dynamic Neural Network and Deep Learning M. Alsarayreh et al.
184. NARX-model-based parameter estimation for batchwise rotary drying processes Y. Wu et al.
185. A Novel Hybrid Algorithms for Groundwater Level Prediction M. Saroughi et al.
186. Prediction of groundwater level and potential zone identification in Keonjhar, Odisha based on machine learning and GIS techniques B. Ritushree et al.
187. A Nonlinear Model of Three-Layer Groundwater Flow with Evaporation Dependent on the Critical Groundwater Level A. Mukhamadiyev et al.
188. Projected changes of groundwater levels in northeastern Romania according to climate scenarios for 2020–2100 L. Sfîcă et al.
189. Deep learning shows declining groundwater levels in Germany until 2100 due to climate change A. Wunsch et al.
190. Assessing groundwater level modelling using a 1-D convolutional neural network (CNN): linking model performances to geospatial and time series features M. Gomez et al.
191. Modified flood potential index (MFPI) for flood monitoring in terrestrial water storage depletion basin using GRACE estimates W. Jiang et al.
192. Trend analysis of Alpine spring discharge: Interplay between climate and discharge characteristics M. Vremec et al.
193. Machine learning-based groundwater flow prediction: a case study of Bina region, Madhya Pradesh, India S. Kumar et al.
194. A wavelet-assisted deep learning approach for simulating groundwater levels affected by low-frequency variability S. Chidepudi et al.
195. A multi-scenario multi-model analysis of regional climate projections in a Central–Eastern European agricultural region: assessing shallow groundwater table responses using an aggregated vertical hydrological model L. Koncsos & G. Murányi
196. A systematic review of neural network applications for groundwater level prediction S. Afful et al.
197. Integrating deep learning and multi-objective optimization for floodwater utilization: a coordinated surface water-groundwater regulation framework for groundwater recovery L. Zhang et al.
198. Performance of long short-term memory networks in predicting athlete injury risk H. Tao et al.
199. Sim-to-Real Transfer of Soft Robotic Navigation Strategies That Learns From the Virtual Eye-in-Hand Vision J. Lai et al.
200. Integrating an interpolation technique and AI models using Bayesian model averaging to enhance groundwater level monitoring N. Wang & Z. Wang
201. Risk of groundwater depletion in Jaipur district, India: a prediction of groundwater for 2028 using artificial neural network M. Mondal
202. Daily Groundwater Level Prediction and Uncertainty Using LSTM Coupled with PMI and Bootstrap Incorporating Teleconnection Patterns Information H. Chu et al.
203. Strategic imputation of groundwater data using machine learning: Insights from diverse aquifers in the Chao-Phraya River Basin Y. Sharma et al.
204. Conceptualizing future groundwater models through a ternary framework of multisource data, human expertise, and machine intelligence C. Zhan et al.
205. Efficient evaluation of the thermal performance of deep borehole heat exchangers affected by groundwater seepage Z. Ba et al.
206. Long short-term memory models to quantify long-term evolution of streamflow discharge and groundwater depth in Alabama H. Gholizadeh et al.
207. A ConvLSTM Conjunction Model for Groundwater Level Forecasting in a Karst Aquifer Considering Connectivity Characteristics F. Guo et al.
208. A Machine learning framework to predict reverse flow and water level: A case study of Tonle Sap Lake K. Morovati et al.
209. Hybrid residual modeling of pan evaporation in hyper-arid climates: Benchmarking interpretable neural architectures against physical drivers A. Alsumaiei
210. Groundwater-level prediction in Visakhapatnam district, Andhra Pradesh, India, using Bayesian Neural Networks R. Rajesh et al.
211. Are Neural Networks the Right Tool for Process Modeling and Control of Batch and Batch-like Processes? M. Rashid & P. Mhaskar
212. Prediction of groundwater level under the influence of groundwater exploitation using a data-driven method with the combination of time series analysis and long short-term memory: a case study of a coastal aquifer in Rizhao City, Northern China B. Guo et al.
213. Advance prediction of coastal groundwater levels with temporal convolutional and long short-term memory networks X. Zhang et al.
214. Deep dive into hydrologic simulations at global scale: harnessing the power of deep learning and physics-informed differentiable models (δHBV-globe1.0-hydroDL) D. Feng et al.
215. Long Short-Term Memory-Based Temporal Modeling for Carnosic Acid Peak Prediction in Rosmarinus officinalis: A Deep Learning Approach, Biological Potential, and Molecular Docking M. Rafya et al.
216. Granger-guided reduced dual attention long short-term memory for travel demand forecasting during coronavirus disease 2019 Y. Zhang et al.
217. Predicting Changes in Spatiotemporal Groundwater Storage Through the Integration of Multi-Satellite Data and Deep Learning Models J. Seo & S. Lee
218. Regional groundwater sequential forecasting using global and local LSTM models S. Patra et al.
219. Evaluate effect of 126 pre-processing methods on various artificial intelligence models accuracy versus normal mode to predict groundwater level (case study: Hamedan-Bahar Plain, Iran) M. Saroughi et al.
220. Enhancing flood forecasts: A comprehensive neural network approach for groundwater flooding in lowland karst areas R. Tabbussum et al.
221. Use of meta-heuristic approach in the estimation of aquifer's response to climate change under shared socioeconomic pathways N. Zeydalinejad & R. Dehghani
222. A deep CNN-LSTM model for predicting interface depth from gravity data over thrust and fold belts of North East India S. Maiti & R. Chiluvuru
223. The contribution of remote sensing and input feature selection for groundwater level prediction using LSTM neural networks in the Oum Er-Rbia Basin, Morocco T. Bouramtane et al.
224. Spatial-temporal graph neural networks for groundwater data M. Taccari et al.
225. A comparison between numerical, neural network, and hybrid modelling approaches to simulate spring flow from a karst catchment in northwest Ireland using long-term hydrological data N. Chowdhury et al.
226. Enhancing Shaft Voltage Mitigation with Diffusion Models: A Comprehensive Review for Industrial Electric Motors Z. Abbas et al.
227. Interpretable knowledge-driven framework for groundwater regime simulation: Integrating physical laws and graph-based reasoning for regional groundwater management Y. Dai et al.
228. Graph Neural Network Framework for Spatiotemporal Groundwater Level Forecasting X. Liang et al.
229. Differentiable, Learnable, Regionalized Process‐Based Models With Multiphysical Outputs can Approach State‐Of‐The‐Art Hydrologic Prediction Accuracy D. Feng et al.
230. 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 M. Nafouanti et al.
231. A Hybrid Data Fusion Approach to AI-Assisted Indirect Centralized Integrated SINS/GNSS Navigation System During GNSS Outage E. Abdolkarimi et al.
232. Refining Groundwater Level Prediction with Kolmogorov–Arnold Architectures: A Dual Temporal–Frequency Domain Perspective F. Granata et al.
233. Predicting the Spatial-Temporal Distribution of Human Brucellosis in Europe Based on Convolutional Long Short-Term Memory Network L. Shen et al.