Articles | Volume 16, issue 11
https://doi.org/10.5194/hess-16-4417-2012
© Author(s) 2012. This work is distributed under the Creative Commons Attribution 3.0 License.
26 Nov 2012
A hybrid model of self organizing maps and least square support vector machine for river flow forecasting
Related subject area
Subject: Rivers and Lakes | Techniques and Approaches: Mathematical applications
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Cited articles
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Affandi, A. K. and Watanabe, K.: Daily groundwater level fluctuation forecasting using soft computing technique, Nat. Sci., 5, 1–10, 2007.
Aqil, M., Kita, K., and Macalino, M.: A Preliminary study on the suitability of data driven approach for continuous water laeve modeling, Int. J. Comp. Sci., 1, 246–252, 2006.
Asefa, T., Kemblowski, M., McKee, M., and Khalil, A.: Multi-time scale stream flow predictions: The support vector machines approach, J. Hydrol., 318, 7–16, 2006.
Behzad, M., Asghari, K., Eazi, M., and Palhang, M.: Generalization performance of support vector machines and neural networks in runoff modeling, Expert Syst. Appl., 36, 7624–7629, 2009.
