The combination of forecasts is a well established procedure for improving forecast performance and decreasing the risk of selecting an inferior model out of an existing pool of models. Work in this area mainly focuses on combining several functionally different models, but some publications...

Forecasting is at the heart of every revenue management system, providing necessary input to capacity control, pricing and overbooking functionalities. For airlines, the key to efficient capacity control is determining the time of when to restrict bookings in a lower-fare class to leave space...

In research of time series forecasting, a lot of uncertainty is still related to the task of selecting an appropriate forecasting method for a problem. It is not only the individual algorithms that are available in great quantities; combination approaches have been equally popular in the last...

There are no algorithms that generally perform better or worse than random when looking at all possible data sets according to the no-free-lunch theorem. A specific forecasting method will hence naturally have different performances in different empirical studies. This makes it impossible to...

Am 20. Januar 2021 wird Joe Biden als der 46. Präsident der USA ins Weiße Haus einziehen. Mit dem Machtwechsel in Washington werden in Deutschland und in Europa große Erwartungen und Hoffnungen verbunden. Viele versprechen sich eine Entspannung der transatlantischen Beziehungen sowie die...

In this paper we provide a theoretical analysis of effects of applying different forecast diversification methods on the structure of the forecast error covariance matrices and decomposed forecast error components based on the bias- variance- Bayes error decomposition of James and Hastie. We...

In this paper we provide experimental results and extensions to our previous theoretical findings concerning the combination of forecasts that have been diversified by three different methods: with parameters learned at different data aggregation levels, by thick modeling and by the use of...

The parameter in negative correlation learning (NC) controls the degree of co-operation between individual networks. This paper looks at the way the choice of in the NC algorithm affects the complexity of the function NC can fit, and shows that it acts as a complexity control allowing smooth...

This paper provides a description and experimental comparison of different forecast combination techniques for the application of Revenue Management forecasting for Airlines. In order to benefit from the advantages of forecasts predicting seasonal demand using different forecast models on...