Weighted on-line SVM regression algorithm and its application

Lecture Notes in Computer Science

Volumn 3610, Issue PART I, 2005, Pages 716-719

  Wang, Hui ^a   Pi, Daoying ^a   Sun, Youxian ^a  

^a STATE KEY LABORATORY OF INDUSTRIAL CONTROL TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; DATA STORAGE EQUIPMENT; MATHEMATICAL MODELS; REGRESSION ANALYSIS; TIME VARYING SYSTEMS;

COMPUTER MEMORY; ON-LINE TRAINING ALGORITHM; REDUNDANT SAMPLES; SVM REGRESSION ALGORITHMS;

LAGRANGE MULTIPLIERS;

EID: 26844455318     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11539087_95     Document Type: Conference Paper

References (6)

1. Vapnik, V.N.: The nature of statistical learning theory. Berlin: Springer (1995)
2. Smola, A.J., Schölkopf, B.: A tutorial on support vector regression. Neurocolt technical report. Royal Holloway College, Unisversity of London (1998)
3. Müller, K.R., Smola, A.J.: Predicting time series with support vector machines. Proceedings of ICANN'97, Springer LNCS 1327 (1997) 999-1004
4. Cauwenberghs, G., Poggio, T.: Incremental and decremental support vector Machine. Advances in Neural Information Processing Systems, Vol.13 (2001) 409-415
5. Junshui Ma, James Theiler, and Simon Perkins: Accurate On-line Support Vector Regression. Neural Computation, Vol. 15, Issue 11 (2003) 2683-2704
6. Narendra, K.S., Parthasarathy. K. : Identification and control of dynamic systems using neural networks. IEEE Transactions on Neural Networks, I (2000) 4-27.