11 citations as recorded by crossref.

1. Modelling point-of-consumption residual chlorine in humanitarian response: Can cost-sensitive learning improve probabilistic forecasts? M. De Santi et al. 10.1371/journal.pwat.0000040
2. A novel long-short term memory network approach for stress model updating for excavations in high stress environments J. Morgenroth et al. 10.1080/17499518.2023.2182889
3. EVALUATION OF APPLICABILITY OF DATA AUGMENTATION METHOD FOR DAM INFLOW PREDICTION USING DEEP LEARNING M. HITOKOTO et al. 10.2208/jscejhe.78.2_I_175
4. Simulated annealing coupled with a Naïve Bayes model and base flow separation for streamflow simulation in a snow dominated basin H. Tongal & M. Booij 10.1007/s00477-022-02276-1
5. Combining Synthetic and Observed Data to Enhance Machine Learning Model Performance for Streamflow Prediction S. López-Chacón et al. 10.3390/w15112020
6. Modeling flood susceptibility zones using hybrid machine learning models of an agricultural dominant landscape of India S. Saini et al. 10.1007/s11356-023-29049-9
7. APPLICATION OF DEEP LEARNING TO DAM INFLOW FORECASTS WITH DIFFERENT CHARACTERISTICS IN THE CHUBU AREA AND THE EFFECT OF FORECAST ACCURACY CAUSED BY MIX OF INPUT RAINFALL TYPES T. KUREBAYASHI et al. 10.2208/jscejj.23-16182
8. Monthly streamflow forecasting for the Hunza River Basin using machine learning techniques S. Khan et al. 10.2166/wpt.2023.124
9. Predicting River Discharge in the Niger River Basin: A Deep Learning Approach S. Ogunjo et al. 10.3390/app14010012
10. Influence of resampling techniques on Bayesian network performance in predicting increased algal activity M. Zeinolabedini Rezaabad et al. 10.1016/j.watres.2023.120558
11. Flood susceptibility mapping using ANNs: a case study in model generalization and accuracy from Ontario, Canada R. Khalid & U. Khan 10.1080/10106049.2024.2316653