Time series, ensembles, fuzzy rules

There is no individual forecasting method that is generally for any given time series better than any other method. There always exists a danger that for a given time series the method is inappropriate. To overcome such a problem, distinct ensemble techniques that combine more forecasting methods are designed. These techniques construct a forecast as a (linear) combination of forecasts by individual methods. This contribution provides a novel ensemble technique that determines the weights based on time series features. The knowledge how to determine weights comes from the regression analysis. In order to capture the desirable issues of robustness and mainly of interpretability, the knowledge how to combine individual methods is encoded in a linguistic description. The mechanism of determination of particular weights is PbLD -- a unique fuzzy inference technique . An experimental justification is provided in order to confirm the promising potential of the given direction of research.