Methodological advances in artificial neural networks for time series forecasting
Fecha
2014-06-01
Autores
Cogollo, M. R.
Velasquez, J. D.
Título de la revista
ISSN de la revista
Título del volumen
Editor
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Resumen
Objective: The aim of this paper is to analyze the development of new forecasting models based on neural networks. Method: We used the systematic literature review method employing a manual search of papers published on new neural networks models in the time period 2000 to 2010. Results: Only 18 studies meet all the requirements of the inclusion criteria. Of these, only three proposals considered a neural networks model using a process different to the autoregressive. Conclusion: Although studies relating to the application of neural network models were frequently present, we find that the studies proposing new forecasting models based on neural networks with a theoretical support and a systematic procedure for the construction of model, were scarce in the time period 2000-2010. © 2012 IEEE.