Title :
A systematic solution for the NN3 Forecasting Competition problem based on an ensemble of MLP neural networks
Author :
Adeodato, J.L. ; Vasconcelos, G.C. ; Arnaud, A.L. ; Cunha, R. C L V ; Monteiro, D. S M P
Author_Institution :
NeuroTech Ltd. & Center for Inf., Fed. Univ. of Pernambuco, Recife
Abstract :
This work presents an award winning approach for solving the NN3 forecasting competition problem. It consisted of predicting 18 future values of 111 monthly short time series. This approach consists of applying the median value of a 15-MLP ensemble for predicting each time series. The system performed very well on test data, finishing as the second best solution of the competition with a SMAPE=16.17%.
Keywords :
mathematics computing; multilayer perceptrons; time series; MLP neural network ensemble; NN3 forecasting competition problem; time series; Artificial neural networks; Finishing; Informatics; Neural networks; Performance analysis; Performance evaluation; Phase measurement; Predictive models; System testing; Time series analysis;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761812
