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Combining Singular-Spectrum Analysis and neural networks for time series forecasting (1995)

Lisi, F. ; Nicolis, O. ; Sandri, Marco

Springer

Neural processing letters 2 (1995), S. 6-10

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ISSN: 1573-773X

Source: Springer Online Journal Archives 1860-2000

Topics: Computer Science

Notes: Abstract In this paper, we propose a combination of an adaptive noise-reduction algorithm based on Singular-Spectrum Analysis (SSA) and a standard feedforward neural prediction model. We test the forecast skill of our method on some short real-world and computergenerated time series with different amounts of additive noise. The results show that our combined technique has better performances than those offered by the same network directly applied to raw data, and therefore is well suited to forecast short and noisy time series with an underlying deterministic data generating process (DGP).

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1007/BF02279931

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