Multistage RBF neural network ensemble learning for exchange rates forecasting

Neurocomputing

Volumn 71, Issue 16-18, 2008, Pages 3295-3302

  Yu, Lean ^a,b   Lai, Kin Keung ^b   Wang, Shouyang ^a  

^a INSTITUTE OF SYSTEMS SCIENCE   (China)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Conditional generalized variance; Ensemble learning; Exchange rates prediction; RBF neural networks

Indexed keywords

FEEDFORWARD NEURAL NETWORKS; FORECASTING; IMAGE CLASSIFICATION; RADIAL BASIS FUNCTION NETWORKS; VEGETATION;

CONDITIONAL GENERALIZED VARIANCE; ENSEMBLE LEARNING; ENSEMBLE MEMBERS; ENSEMBLE MODELS; EXCHANGE RATES; EXCHANGE RATES PREDICTION; FORECASTING MODELS; GENERALIZED VARIANCES; MINIMIZATION METHODS; NEURAL NETWORK ENSEMBLES; RADIAL BASIS FUNCTION NEURAL NETWORKS; RBF NETWORKS; RBF NEURAL NETWORKS;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; COMPUTER PREDICTION; CONFERENCE PAPER; CONTROLLED STUDY; DECISION SUPPORT SYSTEM; FINANCE; INTERMETHOD COMPARISON; INVESTMENT; MARKET; NETWORK LEARNING; PREDICTION AND FORECASTING; PRIORITY JOURNAL;

EID: 56549097547     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2008.04.029     Document Type: Conference Paper

References (24)

1. J.A. Benediktsson, J.R. Sveinsson, O.K. Ersoy, and P.H. Swain Parallel consensual neural networks IEEE Trans. Neural Networks 8 1997 54 64
2. C.M. Bishop Improving the generalization properties of radial basis function neural networks Neural Comput. 3 1991 579 588
3. C.M. Bishop Neural Networks for Pattern Recognition 1995 Oxford University Press
4. L. Breiman, Bias, variance, and arcing classifiers, Technical Report TR460, Department of Statistics, University of California, 1994.
5. L. Breiman Bagging predictors Mach. Learn. 24 1996 123 140
6. J. Carney, and P. Cunningham Tuning diversity in bagged ensembles Int. J. Neural Syst. 10 2000 267 280
7. S. Chen, S.A. Billings, C.F.N. Cowan, and P.M. Grant Nonlinear systems identification using radial basis functions Int. J. Syst. Sci. 21 1990 2513 2539
8. L.K. Hansen, and P. Salamon Neural network ensembles IEEE Trans. Pattern Anal. Mach. Intell. 12 1990 993 1001
9. B.H. Kang Unstable weights in the combination of forecasts Manage. Sci. 32 1986 683 695
10. A. Krogh, and J. Vedelsby Neural network ensembles, cross validation, and active learning G. Tesauro D. Touretzky T. Leen Advances in Neural Information Processing Systems Vol. 7 1995 MIT Press Cambridge, MA 231 238
11. K.K. Lai, L. Yu, S.Y. Wang, and W. Huang A novel nonlinear neural network ensemble model for financial time series forecasting Lect. Notes Comput. Sci. 1991 2006 790 793
12. U. Naftaly, N. Intrator, and D. Horn Optimal ensemble averaging of neural networks Network Comput. Neural Syst. 8 1997 283 296
13. M.P. Perrone, and L.N. Cooper When networks disagree: ensemble methods for hybrid neural networks R.J. Mammone Neural Networks for Speech and Image Processing 1993 Chapman & Hall 126 142
14. B.E. Rosen Ensemble learning using decorrelated neural networks Connection Sci. 8 1996 373 384
15. R.E. Schapire The strength of weak learnability Mach. Learn. 5 1990 197 227
16. A.J.C. Sharkey On combining artificial neural nets Connection Sci. 8 1996 299 314
17. K. Tumer, and J. Ghosh Error correlation and error reduction in ensemble classifiers Connection Sci. 8 1996 385 404
18. N. Ueda Optimal linear combination of neural networks for improving classification performance IEEE Trans. Pattern Anal. Mach. Intell. 22 2000 207 215
19. D.K. Wedding II, and K.J. Cios Time series forecasting by combining RBF networks certainty factors and the Box-Jenkins model Neurocomputing 10 1996 149 168
20. D. Wolpert Stacked generalization Neural Networks 5 1992 241 259
21. J.T. Yao, and C.L. Tan A case study on using neural networks to perform technical forecasting of forex Neurocomputing 34 2000 79 98
22. L. Yu, S.Y. Wang, and K.K. Lai A novel nonlinear ensemble forecasting model incorporating GLAR and ANN for foreign exchange rates Comput. Oper. Res. 32 2005 2523 2541
23. L. Yu, W. Huang, K.K. Lai, and S.Y. Wang A reliability-based RBF network ensemble model for foreign exchange rates prediction I. King ICONIP 2006, Part III, Lecture Notes in Computer Science Vol. 4234 2006 380 389
24. L. Yu, K.K. Lai, S.Y. Wang, and W. Huang A bias-variance-complexity trade-off framework for complex system modeling Lect. Notes Comput. Sci. 3980 2006 518 527