Training artificial neural networks for time series prediction using asymmetric cost functions

ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age

Volumn 5, Issue , 2002, Pages 2374-2380

  Crone, S F ^a  

^a UNIVERSITY OF HAMBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATION THEORY; COSTS; ERRORS; FORECASTING; INFORMATION SCIENCE; NEURAL NETWORKS; TIME SERIES;

ASYMMETRIC COST FUNCTIONS; FORECAST METHOD; FORECASTING PROBLEMS; NEURAL NETWORK TRAINING; STATIONARY TIME SERIES; STATISTICAL ERRORS; SUM OF SQUARED ERRORS; TIME SERIES PREDICTION;

COST FUNCTIONS;

EID: 77954521101     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICONIP.2002.1201919     Document Type: Conference Paper

References (26)

1. G. Arminger, N. Götz, Asymmetric Loss Functions for Evaluating the Quality of Forecasts in Time Series for Goods Management Systems - Technical Report 22/1999, Dortmund, 1999
2. J.S. Armstrong, Strategic Planning and Forecasting Fundamentals, K.Albert (ed.), Strategic Management Handbook, McGraw-Hill, New York, 1983, 2, 2-1-2-32, 1983
3. J.S. Armstrong, Error Measures for Generalizing About Forecasting Methods -Empirical Comparisons, International Journal of Forecasting, 1992, 8, 69-80, 1992
4. J.S. Armstrong, Evaluating Forecasting Methods, in J. S. Armstrong (ed.), Principles of Forecasting - A Handbook for Researchers and Practitioners, Kluwer Academic, Boston, 2001, 443-472, 2001
5. E.M. Azoff, Neural Network Time Series Forecasting of Financial Markets, John Wiley & Sons, New York, 1994
6. C.M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, Oxford, 1995
7. R.G. Brown, Statistical Forecasting for Inventory Control, McGraw-Hill, New York, 1959
8. P.F. Christoffersen, F.X. Diebold, Further Results on Forecasting and Model Selection under Asymmetric Loss, Journal of applied econometrics, 11, 1996, 5, 561-572, 1996
9. P.F. Christoffersen, F.X. Diebold, Optimal prediction under general asymmetric loss, Econometric Theory, 13, 808-817, 1997
10. M.P. Clements, D.F. Hendry (eds.), Forecasting economic time series, Cambridge University Press, Cambridge, 1998
11. C.W.J.Granger, Prediction with a Generalized Cost of Error Function, Operational Research Society (eds.), Operational Research Quarterly, 20, S. 199-207, 1969
12. C.W.J.Granger, Forecasting in Business and Economics, Academic Press, New York, 1980
13. S.J.Hanson, D.J.Burr, Minowski-r Back-Propagation Learning in Connectionist Models with non Euclidian Error Signals, in D.Anderson (ed.), Neural Information Processing Systems, American Institute of Physics, New York, 1987, 348-357, 1987
14. J. Hertz, A. Krogh, R.G. Palmer, Introduction to the Theory of Neural Computation, Addison Wesley, Redwood City, 1991
15. S.D. Krane, The Distinction between Inventory Holding and Stockout Costs - Implications for Target Inventories, Asymmetric adjustment, and the effect of Aggregation on Productions Smoothing, International Economic Review, 35, 1, 117-136, 1994
16. S.Makridakis, S.C.Wheelwright, R.J.Hyndman, Forecasting Methods and Applications, Wiley, New York, 1998
17. A. Parsian, N.S. Farsipour, Estimation of the mean of the selected population under asymmetric loss function, O. Anderson, et al. (eds.), Metrika, International Journal for theoretical and applied statistics, 50, 2, 89-107, 1999
18. R.D. Reed, R.J. Marks II, Neural Smithing - Supervised Learning in Feedforward Artificial Neural Networks, MIT Press, Camebridge, MA, 1998
19. D.E. Rumelhart, G.E. Hinton, R.J. Williams, Learning representations by back-propagating errors - (reprint), in J.A. Anderson, E. Rosenfeld (eds.), Neurocomputing - Foundations of Research, MIT Press, Camebridge, MA, 1, 696-699, 1988
20. J. Schwarze, Statistische Kengroßen zur Ex-Post-Beurteilung von Prognosen - (Prognosefehlermaße), in J. Schwarze (ed.), Angewandte Prognoseverfahren, Neue Wirtschafts-Briefe, Herne, 1980, 317-344, 1980
21. Z. Tang, P.A. Fishwick, Feed-forward Neural Nets as Models for Time Series Forecasting - Technical Report TR91-008 Computer and Information Sciences, University of Florida, 1991
22. F.M. Thiesing, Analyse und Prognose von Zeitreihen mit Neuronalen Netzen, Shaker, Aachen, 1998
23. F.M. Thiesing, O. Vornberger, Sales Forecasting using Neural Networks, IEEE (eds.), Proceedings ICNN'97 - Houston, Texas, 9-12 June 1997, 4, 2125-2128, 1997
24. H.R. Varian, A Bayesian approach to real estate assessment in S. E. Fienberg, A. Zellner (eds.), Studies in Bayesian econometric and statistics in Honor of Leonard J. Savage, North-Holland Publishing, Amsterdam, 195-208, 1975
25. A. Zell, Simulation neuronaler Netze, Oldenbourg, München, 1997
26. T. Zimmerer, Künstliche Neuronale Netze versus ökonometrische und zeitreihenanalytische Verfahren zur Prognose ökonomischer Zeitreihen, Peter Lang, Frankfurt a.M., 1997