Neurocomputing in surface water hydrology and hydraulics: A review of two decades retrospective, current status and future prospects

•Review of neurocomputing methods in surface water hydrology and hydraulic sciences.•Detailed analysis on six relevant topics in surface water hydrology and hydraulics.•Past and current research trends, main findings, and gaps for future exploration.•Problem-specific guidelines and recommendations f...

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Veröffentlicht in:	Journal of hydrology (Amsterdam) Jg. 588; S. 125085
Hauptverfasser:	Zounemat-Kermani, Mohammad, Matta, Elena, Cominola, Andrea, Xia, Xilin, Zhang, Qing, Liang, Qiuhua, Hinkelmann, Reinhard
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.09.2020
Schlagworte:	Artificial intelligence Artificial neural networks fluid mechanics guidelines Hydroinformatics Hydrosciences Machine learning prediction risk assessment rivers sediment transport Soft computing surface water surveys BNN ELM FNN DL HNN DT MLP BSA MLR RNN ANFIS EMD NARX ML DWT FFNN DBNN WA-ANN FSP Artificial neural networks AI MAPE PSO MAE GEP RF WDF-ANN WLSSVR CART CCNN ANN CNN MNLR CGPBANN ENN SRC CHAID HPP GRNN WA GMDH GRU SVM MNN SVR GSA RDNN RBNN WNN RPNN GA MSA NFNN LS-SVR ESN SSC LSTM WBNN Soft computing RMSE SOM FIS ARIMA Machine learning Hydrosciences Hydroinformatics Artificial intelligence DAN2
ISSN:	0022-1694, 1879-2707
Online-Zugang:	Volltext
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