Multi-step ahead nonlinear identification of Lorenz’s chaotic system using radial basis neural network with learning by clustering and particle swarm optimization
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DOI: 10.1016/j.chaos.2006.05.077
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References listed on IDEAS
- Bai, Yanping & Jin, Zhen, 2005. "Prediction of SARS epidemic by BP neural networks with online prediction strategy," Chaos, Solitons & Fractals, Elsevier, vol. 26(2), pages 559-569.
- Fotsin, H.B. & Woafo, P., 2005. "Adaptive synchronization of a modified and uncertain chaotic Van der Pol-Duffing oscillator based on parameter identification," Chaos, Solitons & Fractals, Elsevier, vol. 24(5), pages 1363-1371.
- Yang, Hong Ying & Ye, Hao & Wang, Guizeng & Khan, Junaid & Hu, Tongfu, 2006. "Fuzzy neural very-short-term load forecasting based on chaotic dynamics reconstruction," Chaos, Solitons & Fractals, Elsevier, vol. 29(2), pages 462-469.
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Cited by:
- Li, Fengjun & Xu, Zongben, 2008. "The estimation of simultaneous approximation order for neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 36(3), pages 572-580.
- Janmenjoy Nayak & Bighnaraj Naik, 2018. "A Novel Honey-Bees Mating Optimization Approach with Higher order Neural Network for Classification," Journal of Classification, Springer;The Classification Society, vol. 35(3), pages 511-548, October.
- Ait Maatallah, Othman & Achuthan, Ajit & Janoyan, Kerop & Marzocca, Pier, 2015. "Recursive wind speed forecasting based on Hammerstein Auto-Regressive model," Applied Energy, Elsevier, vol. 145(C), pages 191-197.
- Sangiorgio, Matteo & Dercole, Fabio, 2020. "Robustness of LSTM neural networks for multi-step forecasting of chaotic time series," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
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