50 citations as recorded by crossref.

1. A comparison of monthly precipitation point estimates at 6 locations in Iran using integration of soft computing methods and GARCH time series model S. Mehdizadeh et al. 10.1016/j.jhydrol.2017.09.056
2. Harmonize input selection for sediment transport prediction H. Afan et al. 10.1016/j.jhydrol.2017.07.008
3. RBFNN versus GRNN modeling approach for sub-surface evaporation rate prediction in arid region A. Kamel et al. 10.1016/j.suscom.2021.100514
4. New approach to mimic rheological actual shear rate under wall slip condition R. Chin et al. 10.1007/s00366-018-0670-y
5. A hybrid of ANN and CLA to predict rainfall R. Mohammadpour et al. 10.1007/s12517-018-3804-z
6. Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction H. Afan et al. 10.1016/j.jhydrol.2016.07.048
7. Physics-Guided Deep Learning for Improved Production Forecasting in Unconventional Reservoirs S. Mohd Razak et al. 10.2118/214663-PA
8. Monthly inflow forecasting utilizing advanced artificial intelligence methods: a case study of Haditha Dam in Iraq M. Allawi et al. 10.1007/s00477-021-02052-7
9. Thailand tourism forecasting based on a hybrid of discrete wavelet decomposition and NARX neural network R. Kummong & S. Supratid 10.1108/IMDS-11-2015-0463
10. Optimized River Stream-Flow Forecasting Model Utilizing High-Order Response Surface Method B. Keshtegar et al. 10.1007/s11269-016-1397-4
11. Dynamic Physics-Guided Deep Learning for Long-Term Production Forecasting in Unconventional Reservoirs S. Mohd Razak et al. 10.2118/221474-PA
12. A dynamic artificial neural network for tomato yield prediction R. Salazar et al. 10.17660/ActaHortic.2017.1154.11
13. Hydrological Forecasting Using Artificial Intelligence Techniques 研. 周 10.12677/JWRR.2019.81001
14. Modeling of monthly rainfall and runoff of Urmia lake basin using “feed-forward neural network” and “time series analysis” model J. Farajzadeh et al. 10.1016/j.wri.2014.10.003
15. Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow A. Osman et al. 10.1016/j.jhydrol.2020.124896
16. State-of-the-Art Development of Two-Waves Artificial Intelligence Modeling Techniques for River Streamflow Forecasting W. Tan et al. 10.1007/s11831-022-09763-2
17. Optimised neural network model for river-nitrogen prediction utilizing a new training approach P. Kumar et al. 10.1371/journal.pone.0239509
18. Rainfall forecast based on GPS PWV together with meteorological parameters using neural network models A. Khaniani et al. 10.1016/j.jastp.2020.105533
19. 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. 10.1016/j.gsf.2021.101222
20. Predicting climate change and its impact on future occurrences of vector-borne diseases in West Bengal, India J. Mondal et al. 10.1007/s10668-021-01920-0
21. Application of static and dynamic artificial neural networks for forecasting inflow discharges, case study: Sefidroud Dam reservoir P. Hadiyan et al. 10.1016/j.suscom.2020.100401
22. Skilful rainfall forecasts from artificial neural networks with long duration series and single-month optimization J. Abbot & J. Marohasy 10.1016/j.atmosres.2017.07.015
23. A Multistage Analysis of Predicting Public Resilience of Impactful Social Media Crisis Communication in Flooding Emergencies U. Bukar et al. 10.1109/ACCESS.2022.3176963
24. 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. 10.1007/s11269-017-1726-2
25. Development of advanced artificial intelligence models for daily rainfall prediction B. Pham et al. 10.1016/j.atmosres.2020.104845
26. Matrix Approach for the Seasonal Infectious Disease Spread Prediction H. HIROSE et al. 10.1587/transfun.E98.A.2010
27. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review F. Fahimi et al. 10.1007/s00704-016-1735-8
28. Coastal forecast through coupling of Artificial Intelligence and hydro-morphodynamical modelling P. Kumar & N. Leonardi 10.1080/21664250.2023.2233724
29. Monthly and seasonal hydrological drought forecasting using multiple extreme learning machine models G. Wang et al. 10.1080/19942060.2022.2089732
30. Rainfall modelling using backward generalized estimating equations: a case study for Fasa Plain, Iran M. Bahrami & M. Mahmoudi 10.1007/s00703-019-00715-3
31. Real-time flood forecasting based on a general dynamic neural network framework X. Wan et al. 10.1007/s00477-022-02271-6
32. Review of Nitrogen Compounds Prediction in Water Bodies Using Artificial Neural Networks and Other Models P. Kumar et al. 10.3390/su12114359
33. Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq Z. Yaseen et al. 10.1016/j.jhydrol.2016.09.035
34. Incorporating large-scale atmospheric variables in long-term seasonal rainfall forecasting using artificial neural networks: an application to the Ping Basin in Thailand M. Babel et al. 10.2166/nh.2016.212
35. Improved adaptive neuro-fuzzy inference system with bacterial foraging optimization algorithm for suspended sediment concentration estimation W. Li et al. 10.3233/JIFS-232277
36. Tomato yield prediction in a semi-closed greenhouse R. Salazar et al. 10.17660/ActaHortic.2015.1107.36
37. Assessment and Comparison of Satellite-Based Rainfall Products: Validation by Hydrological Modeling Using ANN in a Semi-Arid Zone S. Rachidi et al. 10.3390/w15111997
38. Towards a time and cost effective approach to water quality index class prediction J. Ho et al. 10.1016/j.jhydrol.2019.05.016
39. Improving the Muskingum Flood Routing Method Using a Hybrid of Particle Swarm Optimization and Bat Algorithm M. Ehteram et al. 10.3390/w10060807
40. Potential of Artificial Intelligence-Based Techniques for Rainfall Forecasting in Thailand: A Comprehensive Review M. Waqas et al. 10.3390/w15162979
41. Prediction of Discharge in a Tidal River Using Artificial Neural Networks H. Hidayat et al. 10.1061/(ASCE)HE.1943-5584.0000970
42. Prediction of Suspended Sediment Load Using Data-Driven Models R. Adnan et al. 10.3390/w11102060
43. Prediction of monthly rainfall in Victoria, Australia: Clusterwise linear regression approach A. Bagirov et al. 10.1016/j.atmosres.2017.01.003
44. Monthly Maximum Accumulated Precipitation Forecasting Using Local Precipitation Data and Global Climate Modes J. Sulaiman et al. 10.20965/jaciii.2014.p0999
45. Rainfall prediction using multiple inclusive models and large climate indices S. Mohamadi et al. 10.1007/s11356-022-21727-4
46. Combining a data-driven approach with seasonal forecast data to predict reservoir water volume in the Mediterranean area A. Francipane et al. 10.1080/02626667.2023.2189521
47. 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 10.1016/j.engappai.2017.09.012
48. Chlorophyll-a Predicting Model Based on Dynamic Neural Network H. Wang et al. 10.1080/08839514.2015.1097142
49. Development of Steady-State and Dynamic Mass and Energy Constrained Neural Networks for Distributed Chemical Systems Using Noisy Transient Data A. Mukherjee & D. Bhattacharyya 10.1021/acs.iecr.4c01429
50. Hybrid Series/Parallel All-Nonlinear Dynamic-Static Neural Networks: Development, Training, and Application to Chemical Processes A. Mukherjee & D. Bhattacharyya 10.1021/acs.iecr.2c03339