Articles | Volume 13, issue 9
https://doi.org/10.5194/hess-13-1555-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.Classification of hydro-meteorological conditions and multiple artificial neural networks for streamflow forecasting
Cited articles
Abrahart, R. J. and See, L.: Comparing neural network and autoregressive moving average techniques for the provision of continuous river flow forecasts in two contrasting catchments, Hydrol. Process., 14(11), 2157–2172, 2000.
Abrahart, R. J. and See, L.: Multi-model data fusion for river flow forecasting: an evaluation of six alternative methods based on two contrasting catchments, Hydrol. Earth Syst. Sci., 6, 655–670, 2002.
Anctil, F., Perrin, Ch., and Andreassian V.: Impact of the length of observed records on the performance of ANN and of conceptual parsimonious rainfall-runoff forecasting models, Environ. Modell. Softw., 19, 357–368, 2004.
ASCE Task Committee on Application of Artificial Neural Networks in Hydrology: Artificial neural networks in hydrology. I: preliminary concepts, J. Hydrol. Eng., 5, 115–123, 2000a.
ASCE Task Committee on Application of Artificial Neural Networks in Hydrology: Artificial neural networks in hydrology II: hydrologic applications, J. Hydrol. Eng., 5, 124–137, 2000b.