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• W2058042004 abstract "A new short-term time series forecasting method based on the identification of skeleton algebraic sequences is proposed in this paper. The concept of the rank of the Hankel matrix is exploited to detect a base fragment of the time series. Particle swarm optimization and evolutionary algorithms are then used to remove the noise and identify the skeleton algebraic sequence. Numerical experiments with an artificially generated and a real-world time series are used to illustrate the functionality of the proposed method." @default.
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• W2058042004 date "2011-05-01" @default.
• W2058042004 modified "2023-10-01" @default.
• W2058042004 title "Short-term time series forecasting based on the identification of skeleton algebraic sequences" @default.
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• W2058042004 doi "https://doi.org/10.1016/j.neucom.2011.02.017" @default.
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