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- W2789432857 abstract "Abstract In this paper, we study the multifractal characteristics and cross-correlation behaviour of Air Pollution Index (API) time series data through multifractal detrended cross-correlation analysis method. We analyse the daily API records of nine air pollutants of the university of Hyderabad campus for a period of three years (2013–2016). The cross-correlation behaviour has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, it is found that the cross-correlation analysis shows anti-correlation behaviour for all possible 36 bivariate time series. We also observe the existence of multifractal nature in all the bivariate time series in which many of them show strong multifractal behaviour. In particular, the hazardous particulate matter PM 2.5 and inhalable particulate matter PM10 shows anti-correlated behaviour with all air pollutants." @default.
- W2789432857 created "2018-03-29" @default.
- W2789432857 creator A5066941672 @default.
- W2789432857 creator A5073381855 @default.
- W2789432857 date "2018-07-01" @default.
- W2789432857 modified "2023-09-29" @default.
- W2789432857 title "Multifractal detrended cross-correlation analysis on air pollutants of University of Hyderabad Campus, India" @default.
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- W2789432857 doi "https://doi.org/10.1016/j.physa.2018.02.160" @default.
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