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An analysis of multifractal characteristics of API time series in Nanjing, China

机译:南京市API时间序列的多重分形特征分析

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This paper describes multifractal characteristics of daily air pollution index (API) records in Nanjing from 2001 to 2012. The entire daily API time series is first divided into 12 parts that serve as research objects, and the generalized Hurst exponent is calculated for each series. And then, the multifractal sources are analyzed and singularity spectra are shown. Next, based on a singularity spectrum, the multifractal-characteristics parameters (maximum exponent alpha(0), spectrum width Delta alpha, and asymmetry Delta alpha(as)) are introduced. The results show that the fractality of daily API for each year is multifractal. The multifractal sources originate from both a broad probability density function and different long-range correlations with small and large fluctuations. The strength of the distribution multifractality is stronger than that of the correlation multifractality. The variation in the structure of API time series with increasing years is mainly related to long-range correlations. The structure of API time series in some years is richer. These findings can provide a scientific basis for further probing into the complexity of API. (C) 2016 Elsevier B.V. All rights reserved.
机译:本文描述了2001年至2012年南京市日常空气污染指数(API)记录的多重分形特征。首先将整个日常API时间序列分为12个部分作为研究对象,并对每个系列计算出广义Hurst指数。然后,分析了多重分形源并显示了奇异谱。接下来,基于奇异频谱,引入多重分形特征参数(最大指数alpha(0),频谱宽度Delta alpha和不对称Delta alpha(as))。结果表明,每年API的分形是多重分形的。多重分形源既来自宽泛的概率密度函数,又来自具有小,大波动的不同的长期相关性。分布多重性的强度比相关多重性的强度强。 API时间序列的结构随年份的增加而变化主要与长期相关性有关。几年来,API时间序列的结构更加丰富。这些发现可以为进一步探究API的复杂性提供科学依据。 (C)2016 Elsevier B.V.保留所有权利。

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