Resumo

SALAZAR AGUILAR, María Angélica; MORENO RODRIGUEZ, Guillermo J  e  CABRERA-RIOS, Mauricio. Statistical Characterization and Optimization of Artificial Neural Networks in Time Series Forecasting: The One-Period Forecast Case. Comp. y Sist. [online]. 2006, vol.10, n.1, pp.69-81. ISSN 2007-9737.

Time series forecasting is an active area for the application of Artificial Neural Networks (ANNs). Although the selection of an ANN has been greatly simplified, it remains a challenge to adequately determine the ANN's parameters. In this work a method based on statistical analysis and optimization techniques is proposed to select the ANN's parameters for application in time series forecasting. The results on the successful application of the method in a real demand forecasting problem for the telecommunications industry are also reported.

Palavras-chave : Artificial Neural Networks; Time Series Forecasting; Design and Analysis of Experiments.

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