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Chaotic Features Identification and Analysis in Liujiang River Runoff

机译:柳江流域混沌特征识别与分析

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Because many factors, such as hydrology, riverbed, topography, impose hugely on the evolution of tendency in Liujiang river runoff, so its intrinsic dynamic behavior implied in runoff time series emerges characteristics of dissipative nonlinear systems. This paper firstly presents chaos theory to identify and analyze the time series of Liujiang river runoff. To identify characteristics in different riverbed, season and topography, runoff time series from typical sites and seasons were analyzed in phase space, auto correlation algorithm was employed to analyze the time delay, and the correlation dimension of runoff time series was calculated by Grassberger and Procaccia algorithm. To reduce complexity, small data sets algorithm was adopted to calculate the maximum Lyapunov exponents after the phase space reconstructing. Some crucial conclusions are drawn from chaos theory, and the relationships between evolved tendency of runoff and factors, such as topography and seasons, are deeply analysis.
机译:由于水文,河床,地形等因素极大地影响了柳江径流的趋势演变,因此径流时间序列所隐含的内在动力行为表现出耗散非线性系统的特征。本文首先提出混沌理论来识别和分析柳江径流的时间序列。为了确定不同河床,季节和地形的特征,在相空间中分析了典型站点和季节的径流时间序列,使用自动相关算法分析了时间延迟,并由Grassberger和Procaccia计算了径流时间序列的相关维数。算法。为了降低复杂度,在相空间重构后,采用小数据集算法计算最大Lyapunov指数。从混沌理论中得出了一些关键的结论,并对径流演变趋势与地形和季节等因素之间的关系进行了深入的分析。

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