Scaled UKF-NARX hybrid model for multi-step-ahead forecasting of chaotic time series data
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| 003 | CHVBK | ||
| 005 | 20210128100321.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20151201xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00500-015-1833-z |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-015-1833-z | ||
| 245 | 0 | 0 | |a Scaled UKF-NARX hybrid model for multi-step-ahead forecasting of chaotic time series data |h [Elektronische Daten] |c [Said Abdulkadir, Suet-Peng Yong] |
| 520 | 3 | |a Accurate forecasting is critically important in many time series applications. In this paper, we consider forecasting chaotic problems by proposing a hybrid model composed of scaled unscented Kalman filter with reduced sigma points and non-linear autoregressive network with exogenous inputs, trained using a modified Bayesian regulation backpropagation algorithm. To corroborate developments of the proposed hybrid model, real-life chaotic and simulated time series which are both non-linear in nature are applied to validate the proposed hybrid model. Experiment results show that the proposed hybrid model outperforms other forecasting models reported in the literature in forecasting of chaotic time series. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2015 | ||
| 690 | 7 | |a Chaotic time series |2 nationallicence | |
| 690 | 7 | |a NARX |2 nationallicence | |
| 690 | 7 | |a Hybrid model |2 nationallicence | |
| 690 | 7 | |a Multi-step-ahead forecasting |2 nationallicence | |
| 690 | 7 | |a Scaled UKF-NARX |2 nationallicence | |
| 700 | 1 | |a Abdulkadir |D Said |u Department of Computer and Information Sciences, Universiti Teknologi Petronas (UTP), 31750, Tronoh, Malaysia |4 aut | |
| 700 | 1 | |a Yong |D Suet-Peng |u Department of Computer and Information Sciences, Universiti Teknologi Petronas (UTP), 31750, Tronoh, Malaysia |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/12(2015-12-01), 3479-3496 |x 1432-7643 |q 19:12<3479 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-015-1833-z |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-015-1833-z |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Abdulkadir |D Said |u Department of Computer and Information Sciences, Universiti Teknologi Petronas (UTP), 31750, Tronoh, Malaysia |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Yong |D Suet-Peng |u Department of Computer and Information Sciences, Universiti Teknologi Petronas (UTP), 31750, Tronoh, Malaysia |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/12(2015-12-01), 3479-3496 |x 1432-7643 |q 19:12<3479 |1 2015 |2 19 |o 500 | ||