[1] |
Shen Li-Hua, Chen Ji-Hong, Zeng Zhi-Gang, Jin Jian. Chaotic time series prediction based on robust extreme learning machine. Acta Physica Sinica,
2018, 67(3): 030501.
doi: 10.7498/aps.67.20171887
|
[2] |
Mei Ying, Tan Guan-Zheng, Liu Zhen-Tao, Wu He. Chaotic time series prediction based on brain emotional learning model and self-adaptive genetic algorithm. Acta Physica Sinica,
2018, 67(8): 080502.
doi: 10.7498/aps.67.20172104
|
[3] |
Li Rui-Guo, Zhang Hong-Li, Fan Wen-Hui, Wang Ya. Hermite orthogonal basis neural network based on improved teaching-learning-based optimization algorithm for chaotic time series prediction. Acta Physica Sinica,
2015, 64(20): 200506.
doi: 10.7498/aps.64.200506
|
[4] |
Wang Xin-Ying, Han Min. Multivariate chaotic time series prediction using multiple kernel extreme learning machine. Acta Physica Sinica,
2015, 64(7): 070504.
doi: 10.7498/aps.64.070504
|
[5] |
Zhang Guo-Yong, Wu Yong-Gang, Zhang Yang, Dai Xian-Liang. A simple model for probabilistic interval forecasts of wind power chaotic time series. Acta Physica Sinica,
2014, 63(13): 138801.
doi: 10.7498/aps.63.138801
|
[6] |
Zhang Yu-Mei, Wu Xiao-Jun, Bai Shu-Lin. Chaotic characteristic analysis for traffic flow series and DFPSOVF prediction model. Acta Physica Sinica,
2013, 62(19): 190509.
doi: 10.7498/aps.62.190509
|
[7] |
Zhang Xue-Qing, Liang Jun. Chaotic time series prediction model of wind power based on ensemble empirical mode decomposition-approximate entropy and reservoir. Acta Physica Sinica,
2013, 62(5): 050505.
doi: 10.7498/aps.62.050505
|
[8] |
Zhang Wen-Zhuan, Long Wen, Jiao Jian-Jun. Parameter determination based on composite evolutionary algorithm for reconstructing phase-space in chaos time series. Acta Physica Sinica,
2012, 61(22): 220506.
doi: 10.7498/aps.61.220506
|
[9] |
Li Jun, Zhang You-Peng. Single-step and multiple-step prediction of chaotic time series using Gaussian process model. Acta Physica Sinica,
2011, 60(7): 070513.
doi: 10.7498/aps.60.070513
|
[10] |
Zhang Chun-Tao, Ma Qian-Li, Peng Hong. Chaotic time series prediction based on information entropy optimized parameters of phase space reconstruction. Acta Physica Sinica,
2010, 59(11): 7623-7629.
doi: 10.7498/aps.59.7623
|
[11] |
Ma Qian-Li, Zheng Qi-Lun, Peng Hong, Qin Jiang-Wei. Chaotic time series prediction based on fuzzy boundary modular neural networks. Acta Physica Sinica,
2009, 58(3): 1410-1419.
doi: 10.7498/aps.58.1410
|
[12] |
Liu Fu-Cai, Zhang Yan-Liu, Chen Chao. Prediction of chaotic time series based on robust fuzzy clustering. Acta Physica Sinica,
2008, 57(5): 2784-2790.
doi: 10.7498/aps.57.2784
|
[13] |
Zhang Jun-Feng, Hu Shou-Song. Chaotic time series prediction based on RBF neural networks with a new clustering algorithm. Acta Physica Sinica,
2007, 56(2): 713-719.
doi: 10.7498/aps.56.713
|
[14] |
He Tao, Zhou Zheng-Ou. Prediction of chaotic time series based on fractal self-affinity. Acta Physica Sinica,
2007, 56(2): 693-700.
doi: 10.7498/aps.56.693
|
[15] |
Liu Fu-Cai, Sun Li-Ping, Liang Xiao-Ming. Prediction of chaotic time series based on hierarchical fuzzy-clustering. Acta Physica Sinica,
2006, 55(7): 3302-3306.
doi: 10.7498/aps.55.3302
|
[16] |
Cui Wan-Zhao, Zhu Chang-Chun, Bao Wen-Xing, Liu Jun-Hua. Prediction of the chaotic time series using support vector machines for fuzzy rule-based modeling. Acta Physica Sinica,
2005, 54(7): 3009-3018.
doi: 10.7498/aps.54.3009
|
[17] |
Ye Mei-Ying, Wang Xiao-Dong, Zhang Hao-Ran. Chaotic time series forecasting using online least squares support vector machine regression. Acta Physica Sinica,
2005, 54(6): 2568-2573.
doi: 10.7498/aps.54.2568
|
[18] |
Li Jun, Liu Jun-Hua. On the prediction of chaotic time series using a new generalized radial basis function neural networks. Acta Physica Sinica,
2005, 54(10): 4569-4577.
doi: 10.7498/aps.54.4569
|
[19] |
Wang Hong-Wei, Ma Guang-Fu. Prediction of chaotic time series based on fuzzy model. Acta Physica Sinica,
2004, 53(10): 3293-3297.
doi: 10.7498/aps.53.3293
|
[20] |
Tan Wen, Wang Yao-Nan, Zhou Shao-Wu, Liu Zu-Run. Prediction of the chaotic time series using neuro-fuzzy networks. Acta Physica Sinica,
2003, 52(4): 795-801.
doi: 10.7498/aps.52.795
|