The Ensemble Approach to Forecasting: A Review and Synthesis

This discussion reviews and synthesises the ensemble forecasting approach to modelling. Ensemble forecasting involves combining multiple data sources, models, assumptions, and pattern recognition methods to account for uncertainties. The authors highlight the potential benefits of ensemble forecasting in transport research, arguing that it can improve forecast accuracy and reliability. The document examines various ensemble methods, including combining models, combining data, and ensembles of ensembles, and discusses their applications in different fields. They illustrate the effectiveness of ensemble models in three case studies: residential property prices, for-hire vehicle flow in Chicago, and for-hire vehicle flow in New York City.

Link to the paper: https://ideas.repec.org/p/nex/wpaper/ensembleapproachforecasting.html

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