Time series forecasting using neural networks: Should the data be deseasonalized first?

Journal of Forecasting

Volumn 18, Issue 5, 1999, Pages 359-367

  Nelson, Michael ^a   Hill, Tim ^b,c   Remus, William ^b,d   O'Connor, Marcus ^c  

^a Arthur Andersen & Co   (Australia)

^b UNIVERSITY OF HAWAII   (United States)

^c UNIVERSITY OF NEW SOUTH WALES   (Australia)

^d UNIVERSITY OF HAWAII   (United States)

Author keywords

Back propagation; Neural networks; Seasonality; Time series forecasting; Universal function approximation

Indexed keywords

EID: 0000902316     PISSN: 02776693     EISSN: None     Source Type: Journal    
DOI: 10.1002/(SICI)1099-131X(199909)18:5<359::AID-FOR746>3.0.CO;2-P     Document Type: Article

References (9)

1. Armstrong, J. S. and Collopy, F. 'Error measures for generalizing about forecasting methods: Empirical comparisons', International Journal of Forecasting, 8 (1992), 69-80.
2. Balestrino, A., Bini Verona, F. and Santanche, M. 'Time series analysis by neural networks: Environmental temperature forecasting', Autoniazione e Strummentazione, 42(12) (1994), 81-7.
3. Carbone, R. and Armstrong, J. S. 'Evaluation of extrapolative forecasting methods: Results of academicians and practitioners', Journal of Forecasting, 1 (1982), 215-7.
4. Chakraborty, K., Mehrotra, K., Mohan, C. K. and Ranka, S. 'Forecasting the behavior of multivariate time series using neural networks', Neural Networks, 5 (1992), 961-70.
5. Cybenko, G. 'Approximation by superpositions of a sigmoidal function', Mathematics of Control, Signals, and Systems, 2 (1989), 303-14.
6. Foster, W. R., Collopy, F. and Ungar, L. H. 'Neural network forecasting of short, noisy time series', Computers and Chemical Engineering, 16 (1992), 293-7.
7. Sharda, R. and Patil, R. B. 'Connectionist approach to time series prediction: An empirical test', Journal of Intelligent Manufacturing, 3 (1992), 317-23.
8. Tang, Z., de Almeida, C. and Fishwick, P. A. 'Time series forecasting using neural networks vs. Box-Jenkins methodology', Simulation, 57(5) (1991), 303-10.
9. Wasserman, P. D. Neural Computing: Theory and Practice, New York: Van Nostrand Reinhold, 1989.