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ARRBFNs with SVR for prediction of chaotic time series with outliers

✍ Scribed by Yu-Yi Fu; Chia-Ju Wu; Chia-Nan Ko; Jin-Tsong Jeng; Li-Chun Lai


Book ID
106246680
Publisher
Springer Japan
Year
2009
Tongue
English
Weight
446 KB
Volume
14
Category
Article
ISSN
1433-5298

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Prediction of multivariate chaotic time
✍ Li-yun Su πŸ“‚ Article πŸ“… 2010 πŸ› Elsevier Science 🌐 English βš– 761 KB

To improve the prediction accuracy of complex multivariate chaotic time series, a novel scheme formed on the basis of multivariate local polynomial fitting with the optimal kernel function is proposed. According to Takens Theorem, a chaotic time series is reconstructed into vector data, multivariate