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An Ensemble Technique to Daily Rainfall Forecasting Based on SSA

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1 Author(s)
Jifu Nong ; Coll. of Sci., Guangxi Univ. for Nat., Nanning, China

In this paper, we have proposed a constructive methodology for temporal data learning supported by results and prescriptions related to the embedding theorem, and using the singular spectrum analysis both in order to reduce the effects of the possible discontinuity of the signal and to implement an efficient ensemble method. In this paper we present new results concerning the application of this approach to the forecasting of the individual rainfall intensities series collected by 135 stations. The average RMS error of the obtained forecasting is less than 3 mm of rain.

Published in:

Computational Sciences and Optimization (CSO), 2012 Fifth International Joint Conference on

Date of Conference:

23-26 June 2012