67 citations as recorded by crossref.

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33. Evaluating the substitution potential of SBS with crumb rubber-polypropylene blends as asphalt binder and mixture modifiers D. Nasr et al. 10.1016/j.conbuildmat.2022.129503
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35. Improving Flood Forecasting in a Developing Country: A Comparative Study of Stepwise Multiple Linear Regression and Artificial Neural Network Z. Latt & H. Wittenberg 10.1007/s11269-014-0600-8
36. Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks Y. Chiang et al. 10.5194/hess-15-185-2011
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40. Study on Hydropower Energy and its Future Changes in the Upper Yangtze River Basin under Climate Change X. Zeng et al. 10.4028/www.scientific.net/AMR.648.232
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42. River Suspended Sediment Prediction Using Various Multilayer Perceptron Neural Network Training Algorithms—A Case Study in Malaysia M. Mustafa et al. 10.1007/s11269-012-9992-5
43. A comparison between wavelet based static and dynamic neural network approaches for runoff prediction M. Shoaib et al. 10.1016/j.jhydrol.2016.01.076
44. Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting R. Abrahart et al. 10.1177/0309133312444943
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51. Dynamic rule curves for flood control of a multipurpose dam C. Chaleeraktrakoon & Y. Chinsomboon 10.1016/j.jher.2014.11.002
52. An information theoretic approach to select alternate subsets of predictors for data-driven hydrological models R. Taormina et al. 10.1016/j.jhydrol.2016.07.045
53. The Annual Maximum Flood Peak Discharge Forecasting Using Hermite Projection Pursuit Regression with SSO and LS Method W. Wang et al. 10.1007/s11269-016-1538-9
54. Urban Pluvial Flood Forecasting using Open Data with Machine Learning Techniques in Pattani Basin J. Noymanee et al. 10.1016/j.procs.2017.11.187
55. ANN-based interval forecasting of streamflow discharges using the LUBE method and MOFIPS R. Taormina & K. Chau 10.1016/j.engappai.2015.07.019
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57. Multilayer perceptron with different training algorithms for streamflow forecasting P. Hosseinzadeh Talaee 10.1007/s00521-012-1287-5
58. Forecasting interest rates: a comparative assessment of some second-generation nonlinear models D. Nachane & J. Clavel 10.1080/02664760701835243
59. Evaluation of reservoir sedimentation using data driven techniques V. Garg & V. Jothiprakash 10.1016/j.asoc.2013.04.019
60. An RBF network with a two-step learning algorithm for developing a reservoir inflow forecasting model G. Lin & M. Wu 10.1016/j.jhydrol.2011.05.042
61. Uncertainty analysis of streamflow drought forecast using artificial neural networks and Monte‐Carlo simulation M. Dehghani et al. 10.1002/joc.3754
62. Monthly river flow forecasting by an adaptive neuro-fuzzy inference system M. Firat & M. Turan 10.1111/j.1747-6593.2008.00162.x
63. Modelling nitrogen composition in streams on the Boreal Plain using genetic adaptive general regression neural networks X. Li et al. 10.1139/S08-041
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65. Incorporating Forecasts of Rainfall in Two Hydrologic Models Used for Medium-Range Streamflow Forecasting J. Bravo et al. 10.1061/(ASCE)HE.1943-5584.0000014
66. Multi-criteria validation of artificial neural network rainfall-runoff modeling R. Modarres 10.5194/hess-13-411-2009
67. Neural network model for discharge and water-level prediction for Ramganga River catchment of Ganga Basin, India M. Khan et al. 10.1080/02626667.2015.1083650