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The parametric modified limited penetrable visibility graph for constructing complex networks from time series

机译:用于构建从时间序列的复杂网络的参数修改有限的可视化可见性图

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This paper presents the parametric modified limited penetrable visibility graph (PMLPVG) algorithm for constructing complex networks from time series. We modify the penetrable visibility criterion of limited penetrable visibility graph (LPVG) in order to improve the rationality of the original penetrable visibility and preserve the dynamic characteristics of the time series. The addition of view angle provides a new approach to characterize the dynamic structure of the time series that is invisible in the previous algorithm. The reliability of the PMLPVG algorithm is verified by applying it to three types of artificial data as well as the actual data of natural gas prices in different regions. The empirical results indicate that PMLPVG algorithm can distinguish the different time series from each other. Meanwhile, the analysis results of natural gas prices data using PMLPVG are consistent with the detrended fluctuation analysis (DFA). The results imply that the PMLPVG algorithm may be a reasonable and significant tool for identifying various time series in different fields. (C) 2017 Elsevier B.V. All rights reserved.
机译:本文介绍了从时间序列构建复杂网络的参数化改进的有限可视化可见性图表(PMLPVG)算法。我们修改了有限的可渗透可见性图(LPVG)的可渗透可视性标准,以提高原始可透视可视性的合理性,并保留时间序列的动态特性。添加视角提供了一种新方法来表征在前算法中不可见的时间序列的动态结构。通过将其应用于三种类型的人工数据以及不同地区的天然气价格的实际数据来验证PMLPVG算法的可靠性。经验结果表明,PMLPVG算法可以将不同的时间序列彼此区分开来。同时,使用PMLPVG的天然气价格数据的分析结果与减法的波动分析(DFA)一致。结果意味着PMLPVG算法可以是用于识别不同领域的各种时间序列的合理和重要的工具。 (c)2017年Elsevier B.V.保留所有权利。

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