Algebraic segmentation of short nonstationary time series based on evolutionary prediction algorithms

@article{Palivonaite2013AlgebraicSO,
  title={Algebraic segmentation of short nonstationary time series based on evolutionary prediction algorithms},
  author={Rita Palivonaite and K. Lukoseviciute and M. Ragulskis},
  journal={Neurocomputing},
  year={2013},
  volume={121},
  pages={354-364}
}
  • Rita Palivonaite, K. Lukoseviciute, M. Ragulskis
  • Published 2013
  • Mathematics, Computer Science
  • Neurocomputing
  • Algebraic segmentation of short nonstationary time series is presented in this paper. The proposed algorithm is based on the algebraic one step-forward predictor which is used to identify a temporal near-optimal algebraic model of the real-world time series. A combinatorial algorithm is used to identify intervals where prediction errors are lower than a predefined level of acceptable accuracy. Special deterministic strategy is developed for the selection of this acceptable level of prediction… CONTINUE READING
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