Long-term prediction of nonlinear time series
Description
This paper is about applying recurrent least squares support vector machines (LS-SVM) on three ESTSP08 competition datasets. Least squares
support vector machines are used as nonlinear models in order to avoid local
minima problems. Then prediction task is re-formulated as function approximation
task. Recurrent LS-SVM uses nonlinear autoregressive exogenous (NARX) model
to build nonlinear regressor, by estimating in each iteration the next output value,
given the past output and input measurements.
Resources
| Name |
Format |
Description |
Link |
|
33 |
ESTSP08 |
https://c3.nasa.gov/dashlink/static/media/publication/I._Jaganjac_ESTSP08.pdf |