Abstract Due to the error in the measured value of the initial state and the
sensitive dependence on initial conditions of chaotic dynamical
systems, the error of chaotic time series prediction increases with
the prediction step. This paper provides a method to improve the
prediction precision by adjusting the predicted value in the course
of iteration according to the evolution information of small
intervals on the left and right sides of the predicted value. The
adjusted predicted result is a non-trajectory which can provide
a better prediction performance than the usual result based on the
trajectory. Numerical simulations of two typical chaotic maps
demonstrate its effectiveness. When the prediction step gets
relatively larger, the effect is more pronounced.
Received: 03 September 2008
Revised: 23 February 2009
Published: 20 August 2009
Yan Hua, Wei Ping, Xiao Xian-Ci A method to improve the precision of chaotic time series prediction by using a non-trajectory 2009 Chin. Phys. B 18 03287
