Forecasting time-series by Kohonen classification

In this paper, we propose a generic non-linear approach for time series forecasting. The main feature of this approach is the use of a simple statistical forecasting in small regions of an input space adequately chosen and quantized. The partition of the space is achieved by the Kohonen algorithm. The method is then applied to a widely known time-series from the SantaFe competition, and the results are compared with the best ones published for this series.

• Type: Conference
• Year: 1998
• Where: ESANN
• Authors: Amaury Lendasse, Michel Verleysen, Eric de Bodt, Marie Cottrell, Philippe Grégoire
• Keywords: ESANN 1998, ESANN 2007, Generic Non-linear Approach, Simple Statistical Forecasting, Time Series Forecasting