Application of the 0-1 test algorithm for chaos to runoff time series
The commonly used methods for the identification of chaotic characteristic of runoff time series are the correlation dimension method, the largest Lyapunov exponent method and Kolmogorov entropy method, which are based on the phase space reconstruction. Recently, a novel test approach for chaos detection in time series named zero-one (0-1) test has been proposed. This method applies directly to time series data; therefore, the phase space reconstruction is not required. Moreover, the non-chaotic and chaotic motions can be decided by means of the parameters Kc approaching asymptotically either to zero or one. Case studies of Logistic map, daily runoff series of Jinsha River in China and Umpqua River in America are implemented. The chaotic characteristics are identified and verified by using the 0-1 test algorithm. Then, based on the phase space reconstruction, five nonlinear dynamic methods are employed; ① phase space reconstruction; ② the false Nearest Neighbor ( FNN) algorithm; ③ correlation dimension method; ④ Lyapunov exponent method; and, ⑤ Kolmogorov entropy. The comparative results show the effectiveness and reliability of the 0-1 test algorithm. The results from these methods provide cross-verification and confirmation of the existence of a mild low-dimensional chaos in the two daily runoff time series.
国家科技期刊平台
NSTL
万方数据
