1Takens F. Determining strange attractors in turbulence[A]. Lecture Notes inMathematics[C]. Berlin: Springer, 1981, 898: 361-381.
2Wolf A. Determining Lyapunov exponents from a time series [J]. Physica D, 1985, 16(3): 285-371.
3Rosenstein M T, Collins J J, Deluca C J. A practical method for calculating largest Lyapunov exponents from small data sets[J]. Physica D, 1993, 65(1): 117-134.
4Cao L Y. Practical method for determining the minimum embedding dimension of a scalar time series[J]. Physica D, 1997, 110( 1-2): 43-50.
5Kim H S, Eyldholt R, Salts J D. Nonlinear dynamics, delay times and embedding windows[J]. PhysicaD, 1999, 127(1-2): 48-60.
6Senjyu T, Uezato K. One-hour-ahead load forecasting using neural network[J]. IEEE Trans on PWRS , 2002, 17(1): 113-117.
7Giona M, Cimagalli V, Morgavi G et al. Local prediction of chaotic time series[C]. Proceedings of IEEE Workshop on Nonlinear Signal and Image Proceeding, 1991, 1: 894-897.
8Kantz H, Schreiber T. Nonlinear time series analysis[M]. Cambridge:Cambridge University Press, 1996.
9Cao Liangyue. Practical method for determining the minimum embedding dimension of a scalar time series[J]. Physica D, 1997, (总110): 43-50.
10Zhang J, Man K F. Time series prediction using RNN in multi-dimension embedding phase space[J]. Neural Proceeding Letters, 1998, (7): 1868-1873.
