Neural networks and traditional time series methods: A synergistic combination in state economic forecasts

IEEE Transactions on Neural Networks

Volumn 8, Issue 4, 1997, Pages 863-873

  Hansen, James V ^a   Nelson, Ray D ^a  

^a BRIGHAM YOUNG UNIVERSITY   (United States)

Author keywords

Adaptive expectations; Forecasting; Genetic algorithms; Neural networks; Statistical models; Time series

Indexed keywords

ECONOMICS; GENETIC ALGORITHMS; STATISTICAL METHODS; TIME SERIES ANALYSIS;

STATE ECONOMIC FORECASTS;

NEURAL NETWORKS;

EID: 0031191950     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.595884     Document Type: Article

References (24)

1. G. E. P. Box and G. M. Jenkin, Time Series Analysis: Forecasting and Control. San Francisco, CA: Holden-Day, 1970.
2. D. Chalmers, "The evolution of learning: An experiment in genetic connectionism," Proc. 1990 Connectionist Models Summer School, D. S. Touretzky, J. Elman, and G. Hinton, Eds. San Mateo, CA: Morgan Kaufmann, 1991.
3. R. T. Clemen, "Combining forecasts: A review and annotated bibliography," Int. J. Forecasting, vol. 5, pp. 559-583, 1989.
4. R. B. Cleveland, W. S. Cleveland, J. E. McRae, and I. Terpenning, "STL: A seasonal-trend decomposition procedure based on LOESS," J. Official Statisti., vol. 6, pp. 3-73, 1990.
5. W. S. Cleveland and S. J. Devlin, "Calendar effects in monthly time seres: Modeling and adjustment," J. Amer. Statist. Assoc., vol. 77, pp. 520-528, 1982.
6. _, "Locally-weighted regression: An approach to regression analysis by local fitting," J. Amer. Statist. Assoc., vol. 83, pp. 596-610, 1988.
7. W. S. Cleveland, S. J. Devlin, and I. J. Terpenning, "The SABL statistical and graphical methods," Computing Information Library, Bell Labs, Murray Hill, NJ, 1981.
8. S. Day and M. Davenport, "Continuous-time temporal backpropagation with adaptive time delays," IEEE Trans. Neural Networks, vol. 4, pp. 348-354, 1993.
9. S. Harp, T. Samad, and A. Guha, "Toward the genetic synthesis of neural networks," in Proc. 3rd Int. Conf. Genetic Algorithms, D. Shaffer, Ed. San Mateo, CA: Morgan Kaufmann, 1989.
10. S. Harp, T. Samad, and A. Guha, "Designing application-specific neural networks using the genetic algorithms," Advances in Neural Information Processing Systems 2, D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann, 1990.
11. M. Hassoun, Fundamentals of Artificial Neural Networks. Cambridge, MA: MIT Press, 1995.
12. T. Hill, L. Marquez, M. O'Conner, and W. Remus, "Artificial neural-network models for forecasting and decision making," Int. J. Forecasting, vol. 10, pp. 5-15, 1994.
13. T. Hill, M. O'Connor, and W. Remus, "Neural-network models for time series forecasts," Management Sci., vol. 42, pp. 1082-1092, 1996.
14. C. C. Holt, "Forecasting seasonal and trends by exponentially weighted moving averages," Office of Naval Res., Memorandum 52, 1957.
15. A. Lapedes and R. Farber, "How neural networks work," in Neural Inform. Processing Syst., pp. 442-456, 1988.
16. G. Miller, P. Todd, and S. Hedge, "Designing neural networks using genetic algorithms," in Proc. 3rd Int. Conf. Genetic Algorithms, D. Shaffer, Ed. San Mateo, CA: Morgan Kaufmann, 1989.
17. D. Montana and L. Davis, "Training feedforward networks using genetic algorithms," in Proc. 11th Int. Joint Conf. Artificial Intell., Detroit, MI, 1989, pp. 762-767.
18. P. Newbold and T. Bo, Introductory Business and Economic Forecasting. Cincinnati, OH: South-Western, 1994.
19. S. B. Reynolds, J. M. Mellichamp, and R. E. Smit, "Box-Jenkins forecast model identification," AI Expert, June, pp. 15-28, 1995.
20. A. Waibel, "Modular construction of time-delay neural networks for speech recognition," Neural Computa., vol. 1, pp. 39-46, 1989.
21. Weigand, A., D. Rumelhart, and B. Huberman, "Generalization by weight elimination with application to forecasting," in Advances in Neural Information Processing Systems 3, R. Lippman, J. Moody, and D. S. Touretzky, Eds. San Mateo, CA: Morgan Kaufmann, 1991, pp. 875-882.
22. H. White, "Learning in artificial neural networks: A statistical perspective," Neural Computa., vol. 1, pp. 425-464, 1989.
23. D. Whitley and T. Hanson, "The GENITOR algorithm: Using genetic recombination to optimize neural networks," Computer Sci. Dept., Colorado State Univ., Fort Collins, Tech. Rep., 1989.
24. P. R. Winters, "Forecasting sales by exponentially weighted moving averages," Management Sci., vol. 6, pp. 324-342, 1960.