Using machine learning techniques to combine forecasting methods

Authors:
Ricardo Prudêncio;Teresa Ludermir
Affiliations:
Centro de Informática, Universidade Federal de Pernambuco, Recife, PE, Brazil;Centro de Informática, Universidade Federal de Pernambuco, Recife, PE, Brazil
Venue:
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Year:
2004

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Abstract

We present here an original work that uses machine learning techniques to combine time series forecasts In this proposal, a machine learning technique uses features of the series at hand to define adequate weights for the individual forecasting methods being combined The combined forecasts are the weighted average of the forecasts provided by the individual methods In order to evaluate this solution, we implemented a prototype that uses a MLP network to combine two widespread methods The experiments performed revealed significantly accurate forecasts.