New Trends on Intelligent Systems and Soft Computing 2014

Granada     13 - 14 February, 2014

Automatic time series forecasting

Friday 14 February, 2014

Many applications require a large number of time series to be forecast completely automatically. For example, manufacturing companies often require weekly forecasts of demand for thousands of products at dozens of locations in order to plan distribution and maintain suitable inventory stocks. In these circumstances, it is not feasible for time series models to be developed for each series by an experienced analyst. Instead, an automatic forecasting algorithm is required.

In addition to providing automatic forecasts when required, these algorithms also provide high quality benchmarks that can be used when developing more specific and specialized forecasting models.

I will describe some algorithms for automatically forecasting univariate time series that have been developed over the last 20 years. The role of forecasting competitions in comparing the forecast accuracy of these algorithms will also be discussed.

Finally, I will describe methods for evaluating forecasting algorithms which use the available data as efficiently as possible.

This conference is financed by ...

  • Visiting proffesors mobility program MAS2008-00413 (Ministerio de Innovación y Ciencia)
  • Plan Propio (Universidad de Granada)
  • Dirección General de Política Universitaria