Recurrent Self-Organizing Map (RSOM) is studied in three di erent time series prediction cases. RSOM is used to cluster the series into local data sets, for which corresponding lo...
Timo Koskela, Markus Varsta, Jukka Heikkonen, Kimm...
Abstract. A prediction scheme for spatio-temporal time series is presented that is based on reconstructed local states. As a numerical example the ev olution of a Kuramoto-Sivashin...
In this paper, the problem of time series prediction is studied. A Bayesian procedure based on Gaussian process models using a nonstationary covariance function is proposed. Exper...
- In this paper we propose a new methodology for Cost-Benefit analysis in a multiple time series prediction problem. The proposed model is evaluated in a real world application bas...
Time series data poses a significant variation to the traditional segmentation techniques of data mining because the observation is derived from multiple instances of the same und...