49 citations as recorded by crossref.

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8. Physics-Guided Deep Learning for Improved Production Forecasting in Unconventional Reservoirs S. Mohd Razak et al. https://doi.org/10.2118/214663-PA
9. Monthly inflow forecasting utilizing advanced artificial intelligence methods: a case study of Haditha Dam in Iraq M. Allawi et al. https://doi.org/10.1007/s00477-021-02052-7
10. Thailand tourism forecasting based on a hybrid of discrete wavelet decomposition and NARX neural network R. Kummong & S. Supratid https://doi.org/10.1108/IMDS-11-2015-0463
11. Optimized River Stream-Flow Forecasting Model Utilizing High-Order Response Surface Method B. Keshtegar et al. https://doi.org/10.1007/s11269-016-1397-4
12. Dynamic Physics-Guided Deep Learning for Long-Term Production Forecasting in Unconventional Reservoirs S. Mohd Razak et al. https://doi.org/10.2118/221474-PA
13. A dynamic artificial neural network for tomato yield prediction R. Salazar et al. https://doi.org/10.17660/ActaHortic.2017.1154.11
14. Hydrological Forecasting Using Artificial Intelligence Techniques 研. 周 https://doi.org/10.12677/JWRR.2019.81001
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17. State-of-the-Art Development of Two-Waves Artificial Intelligence Modeling Techniques for River Streamflow Forecasting W. Tan et al. https://doi.org/10.1007/s11831-022-09763-2
18. Optimised neural network model for river-nitrogen prediction utilizing a new training approach P. Kumar et al. https://doi.org/10.1371/journal.pone.0239509
19. Rainfall forecast based on GPS PWV together with meteorological parameters using neural network models A. Khaniani et al. https://doi.org/10.1016/j.jastp.2020.105533
20. A predictive equation for residual strength using a hybrid of subset selection of maximum dissimilarity method with Pareto optimal multi-gene genetic programming H. Riahi-Madvar et al. https://doi.org/10.1016/j.gsf.2021.101222
21. Predicting climate change and its impact on future occurrences of vector-borne diseases in West Bengal, India J. Mondal et al. https://doi.org/10.1007/s10668-021-01920-0
22. Application of static and dynamic artificial neural networks for forecasting inflow discharges, case study: Sefidroud Dam reservoir P. Hadiyan et al. https://doi.org/10.1016/j.suscom.2020.100401
23. Skilful rainfall forecasts from artificial neural networks with long duration series and single-month optimization J. Abbot & J. Marohasy https://doi.org/10.1016/j.atmosres.2017.07.015
24. A Multistage Analysis of Predicting Public Resilience of Impactful Social Media Crisis Communication in Flooding Emergencies U. Bukar et al. https://doi.org/10.1109/ACCESS.2022.3176963
25. An Integration of Stationary Wavelet Transform and Nonlinear Autoregressive Neural Network with Exogenous Input for Baseline and Future Forecasting of Reservoir Inflow S. Supratid et al. https://doi.org/10.1007/s11269-017-1726-2
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27. Matrix Approach for the Seasonal Infectious Disease Spread Prediction H. HIROSE et al. https://doi.org/10.1587/transfun.E98.A.2010
28. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review F. Fahimi et al. https://doi.org/10.1007/s00704-016-1735-8
29. Coastal forecast through coupling of Artificial Intelligence and hydro-morphodynamical modelling P. Kumar & N. Leonardi https://doi.org/10.1080/21664250.2023.2233724
30. Monthly and seasonal hydrological drought forecasting using multiple extreme learning machine models G. Wang et al. https://doi.org/10.1080/19942060.2022.2089732
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36. Improved adaptive neuro-fuzzy inference system with bacterial foraging optimization algorithm for suspended sediment concentration estimation W. Li et al. https://doi.org/10.3233/JIFS-232277
37. Tomato yield prediction in a semi-closed greenhouse R. Salazar et al. https://doi.org/10.17660/ActaHortic.2015.1107.36
38. Assessing the Performance of Ensemble and Regularized Models for Daily Rainfall Forecasting in Singapore M. Musliadi et al. https://doi.org/10.60084/ijds.v3i2.360
39. Assessment and Comparison of Satellite-Based Rainfall Products: Validation by Hydrological Modeling Using ANN in a Semi-Arid Zone S. Rachidi et al. https://doi.org/10.3390/w15111997
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41. Improving the Muskingum Flood Routing Method Using a Hybrid of Particle Swarm Optimization and Bat Algorithm M. Ehteram et al. https://doi.org/10.3390/w10060807
42. Potential of Artificial Intelligence-Based Techniques for Rainfall Forecasting in Thailand: A Comprehensive Review M. Waqas et al. https://doi.org/10.3390/w15162979
43. Prediction of Discharge in a Tidal River Using Artificial Neural Networks H. Hidayat et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000970
44. Prediction of Suspended Sediment Load Using Data-Driven Models R. Adnan et al. https://doi.org/10.3390/w11102060
45. Prediction of monthly rainfall in Victoria, Australia: Clusterwise linear regression approach A. Bagirov et al. https://doi.org/10.1016/j.atmosres.2017.01.003
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48. Combining a data-driven approach with seasonal forecast data to predict reservoir water volume in the Mediterranean area A. Francipane et al. https://doi.org/10.1080/02626667.2023.2189521
49. Optimization of neural network using kidney-inspired algorithm with control of filtration rate and chaotic map for real-world rainfall forecasting N. Jaddi & S. Abdullah https://doi.org/10.1016/j.engappai.2017.09.012