Time series forecasting using a perturbative intelligent system

Authors:
Paulo S.G. de Mattos Neto;Aranildo R. Lima Junior;Tiago A.E. Ferreira
Affiliations:
Federal University of Pernambuco, Recife, Brazil;The University of British Columbia, Vancouver, Canada;Federal Rural University of Pernambuco, Recife, Brazil
Venue:
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Year:
2010

Citing 3
Cited 1

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Abstract

The Perturbative Time-delay Added Evolutionary Forecasting (P-TAEF) method for time series prediction is inspired in the Perturbation Theory, a concept already commonly used in other areas of science (physics, mathematics, etc), and evolutionary computing. This methodology is shown and an experimental investigation is conducted with some relevant time series and the results achieved are discussed and compared with previous results found in the literature.