2021-04-122014-06-0115480992WOS;000341576900031SCOPUS;2-s2.0-84905750098http://hdl.handle.net/10784/27754Objective: 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.spahttps://v2.sherpa.ac.uk/id/publication/issn/1548-0992articleNeural networksTime seriesANFISARIMAConstruction of modelsNeural network modelNeural networks modelNonlinear time seriesSystematic literature reviewTime series forecastingForecasting2021-04-12Cogollo, M. R.Velasquez, J. D.10.1109/TLA.2014.6868881