Services on Demand
Journal
Article
Indicators
- Cited by SciELO
- Access statistics
Related links
- Similars in SciELO
Share
Ingeniería, investigación y tecnología
On-line version ISSN 2594-0732Print version ISSN 1405-7743
Abstract
ACOSTA-CERVANTES, M.C.; VILLARREAL-MARROQUIN, M.G. and CABRERA-RIOS, M.. Validation Study on Artificial Neural Network-Based Selection of Time Series Forecasting Techniques. Ing. invest. y tecnol. [online]. 2013, vol.14, n.1, pp.53-63. ISSN 2594-0732.
In this paper, a validation study for a method geared towards the selection of forecasting techniques for time series is presented. The proposed method makes use of artificial neural networks to predict the performance of several statistics-based forecasting techniques to help select the potential best one. Eighteen time series with real data related to economic activities in the state of Tamaulipas were used for validation purposes. The results indicate that the proposed method is sufficiently reliable to become a useful resource for people with modest level of training in statistics. It is also proposed that the method be tabulated for convenient access.
Keywords : Artificial Neural Network (ANN); forecasting methods; time series.