Abstract
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.
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Ding, H., Dong, W., Wu, D. (2014). Chaotic Features Identification and Analysis in Liujiang River Runoff. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_71
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DOI: https://doi.org/10.1007/978-3-319-09333-8_71
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09332-1
Online ISBN: 978-3-319-09333-8
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