Please use this identifier to cite or link to this item: http://repositorio.lnec.pt:8080/jspui/handle/123456789/1002862
Title: An enhanced blend of SVM and Cascade methods for short-term rainfall forecasting
Authors: Wang, L.
Simões, N. E.
Ochoa, S.
Leitão, J. P.
Pina, R.
Onof, C.
Sá Marques, A.
Maksimovic, C.
Carvalho, R.
David, L. M.
Keywords: Support vector machine;Cascade;Log-poisson;Rainfall forecasting;Downscaling
Issue Date: Sep-2011
Publisher: IWA
Abstract: A more reliable flood forecasting could benefit from higher-resolution rainfall forecasts as inputs. However, the prediction lead time of the operational rainfall forecasting models will substantially diminish while sub-hourly (e.g., 5-min) rainfall forecasting is required. A method that integrates the SVM (Support Vector Machine) and Cascade-based downscaling techniques is therefore developed in this work to carry out high-resolution (5-min) precipitation forecasting with longer lead time (45-60 minutes). The 5-min raingauge observations from Coimbra (Portugal) are employed to assess the proposed methodology. A comparison with the conventional SVM is also conducted to study the possible benefit of using the proposed methodology to carry out shortterm rainfall forecasting.
URI: http://repositorio.lnec.pt:8080/jspui/handle/123456789/1002862
Appears in Collections:DHA/NES - Comunicações a congressos e artigos de revista

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