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https://www.researchgate.net/publication/3711600_Nonlinear_prediction_of_chaotic_time_series_using_support_vector_machines
Nonlinear prediction of chaotic time series using support vector machines. ... The nonlinear regression estimation issues are solved by successful application of a novel neural network technique ...
https://ieeexplore.ieee.org/document/622433/
Nonlinear prediction of chaotic time series using support vector machines Abstract: A novel method for regression has been recently proposed by Vapnik et al. (1995, 1996). The technique, called support vector machine (SVM), is very well founded from the mathematical point of view and seems to provide a new insight in function approximation.
https://www.sciencedirect.com/science/article/pii/S0169743903001114
Nov 28, 2003 · The goal of this paper is to use a support vector machine (SVM) for the task of time series prediction. SVM is a relatively new nonlinear technique in the field of chemometrics and it has been shown to perform well for classification tasks [2] , regression [3] and time series prediction [4] .Cited by: 427
https://www.sciencedirect.com/science/article/pii/S0925231203003722
S. Mukherjee, E. Osuna, F. Girosi, Nonlinear prediction of chaotic time series using support vector machines, in: Proceedings of the IEEE Workshop on Neural Networks for Signal Processing, Amelia Island, FL, 1997, pp. 511–520.Cited by: 1474
https://www.researchgate.net/publication/2822946_Nonlinear_Prediction_of_Chaotic_Time_Series_Using_Support_Vector_Machines
Nonlinear Prediction of Chaotic Time Series Using Support Vector Machines ... long-term dependencies in time series. For the task of short-term prediction, addressed in this paper, learning the ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.29.6750
BibTeX @INPROCEEDINGS{Mukherjee97nonlinearprediction, author = {Sayan Mukherjee and Edgar Osuna and Federico Girosi}, title = {Nonlinear Prediction of Chaotic Time Series Using Support Vector Machines}, booktitle = {IEEE Workshop on Neural Networks for Signal Processing VII}, year = {1997}, pages = {511--519}, publisher = {IEEE Press}}
https://www.researchgate.net/publication/223045088_Using_support_vector_machines_for_time_series_prediction
Using support vector machines for time series prediction Article in Chemometrics and Intelligent Laboratory Systems 69(1-2):35-49 · November 2003 with 343 Reads How we measure 'reads'
https://www.semanticscholar.org/paper/Nonlinear-prediction-of-chaotic-time-series-using-Mukherjee-Osuna/d81512c6c2582fa91fe151efdaf80a867f66d12a
Nonlinear prediction of chaotic time series using support vector machines @article{Mukherjee1997NonlinearPO, title={Nonlinear prediction of chaotic time series using support vector machines}, author={Sayan Mukherjee and E. R. Freund Osuna and Federico Girosi}, journal={Neural Networks for Signal Processing VII.
https://www.researchgate.net/publication/231071891_Chaotic_time_series_prediction_using_least_squares_support_vector_machines
We propose a new technique of using the least squares support vector machines (LS-SVMs) for making one-step and multi-step prediction of chaotic time series.
http://www.kernel-machines.org/publications/MukOsuGir97
Nonlinear Prediction of Chaotic Time Series using a Support Vector Machine. In: Neural Networks for Signal Processing VII — Proceedings of the 1997 IEEE Workshop, ed. by J. Principe and L. Gile and N. Morgan and E. Wilson, New York, IEEE.
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