Articles | Volume 15, issue 6
https://doi.org/10.5194/hess-15-1835-2011
https://doi.org/10.5194/hess-15-1835-2011
17 Jun 2011
 | 17 Jun 2011

River flow time series using least squares support vector machines

R. Samsudin, P. Saad, and A. Shabri

Related subject area

Subject: Water Resources Management | Techniques and Approaches: Modelling approaches
Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts
Richard Laugesen, Mark Thyer, David McInerney, and Dmitri Kavetski
Hydrol. Earth Syst. Sci., 27, 873–893, https://doi.org/10.5194/hess-27-873-2023,https://doi.org/10.5194/hess-27-873-2023, 2023
Short summary
An improved model of shade-affected stream temperature in Soil & Water Assessment Tool
Efrain Noa-Yarasca, Meghna Babbar-Sebens, and Chris Jordan
Hydrol. Earth Syst. Sci., 27, 739–759, https://doi.org/10.5194/hess-27-739-2023,https://doi.org/10.5194/hess-27-739-2023, 2023
Short summary
Seasonal forecasting of snow resources at Alpine sites
Silvia Terzago, Giulio Bongiovanni, and Jost von Hardenberg
Hydrol. Earth Syst. Sci., 27, 519–542, https://doi.org/10.5194/hess-27-519-2023,https://doi.org/10.5194/hess-27-519-2023, 2023
Short summary
Operationalizing equity in multipurpose water systems
Guang Yang, Matteo Giuliani, and Andrea Castelletti
Hydrol. Earth Syst. Sci., 27, 69–81, https://doi.org/10.5194/hess-27-69-2023,https://doi.org/10.5194/hess-27-69-2023, 2023
Short summary
Evaluation of a new observationally based channel parameterization for the National Water Model
Aaron Heldmyer, Ben Livneh, James McCreight, Laura Read, Joseph Kasprzyk, and Toby Minear
Hydrol. Earth Syst. Sci., 26, 6121–6136, https://doi.org/10.5194/hess-26-6121-2022,https://doi.org/10.5194/hess-26-6121-2022, 2022
Short summary

Cited articles

Abraham, A. and Nath, B.: A neuro-fuzzy approach for modeling electricity demand in Victoria, Appl. Soft Comput., 1(2), 127–138, 2001.
Adamowski, J. and Sun, K.: Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds, J. Hydrol., 390(1–2), 85–91, 2010.
Affandi, A. K. and Watanabe, K.: Daily groundwater level fluctuation forecasting using soft computing technique, Nat. Sci., 5(2), 1–10, 2007.
Afshin, M., Sadeghian, A. and Raahemifar, K.: On efficient tuning of LS-SVM hyper-parameters in short-term load forecasting: A comparative study, Proc. of the 2007 IEEE Power Engineering Society General Meeting (IEEE-PES), 2007.
Akaike, H.: A new look at the statistical model identification, IEEE T. Automat. Contr., 19, 716–723, 1974.
Download