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

F. Lisi, O. Nicolis, Marco Sandri

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

25 Citas (Scopus)


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).

Idioma originalInglés
Páginas (desde-hasta)6-10
Número de páginas5
PublicaciónNeural Processing Letters
EstadoPublicada - 1 jul. 1995

Áreas temáticas de ASJC Scopus

  • Software
  • Neurociencias General
  • Redes de ordenadores y comunicaciones
  • Inteligencia artificial


Profundice en los temas de investigación de 'Combining Singular-Spectrum Analysis and neural networks for time series forecasting'. En conjunto forman una huella única.

Citar esto