Time series prediction via new support vector machines

Proceedings of 2002 International Conference on Machine Learning and Cybernetics

Volumn 1, Issue , 2002, Pages 364-366

  Zhu, Jia Yuan ^a   Ren, Bo ^a   Zhang, Heng Xi ^a   Deng, Zhen Ting ^a  

^a AIR FORCE ENGINEERING UNIVERSITY   (China)

Author keywords

Machine learning; Neural networks; Statistical learning theory; Support vector machines; Time series prediction

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; LEAST SQUARES APPROXIMATIONS; LINEAR EQUATIONS; LINEAR PROGRAMMING; NUMERICAL ANALYSIS; POLYNOMIALS; QUADRATIC PROGRAMMING; RADIAL BASIS FUNCTION NETWORKS; TIME SERIES ANALYSIS;

STATISTICAL LEARNING THEORY; SUPPORT VECTOR MACHINES; TIME SERIES PREDICTION;

LEARNING SYSTEMS;

EID: 0036925049     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. Casdagli M. Nonlinear Prediction of Chaotic Time Series. Physica D, 1989, 35:335-356.
2. kugiumtzis D. Lingiarde O C, Christoph-ersen N. Regularized Local Linear Prediction of Chaotic Time Series. Physica D, 1998, 112; 344-360.
3. Gencay R. Tung Liu. Nonlinear Modeling and Prediction with Feedforward and Recurrent Networks. Physica D, 1997, 108:119-134.
4. G. Deco, D. Obradovic. Decorrelated Hebbian Learning for Clustering and Function Approximation. In Neural Computation, 1995(7), 338-348.
5. J. Platt. Learning by Combining Memorization and Gradient Descent. In Advances in Neural Information Processing Systems, 1996.
6. Maguire L P, Roche B, Mcginnity, T M, Mcdaid L J. Predicting a Chaotic Time Series Using a Fuzzy Neural Network. Information Sciences, 1998, 112:125-136.
7. Vapnik, V. N. Statistical Learning Theory. New York. Springer. 1998.
8. Suykens J.A.K, Vandewalle J, De Moor B. Optimal Control by Least Squares Support Vector Machines. Neural Networks, 2001, Vol. 14(1), 23-35.