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Evolution Mechanism of Atmospheric Pollution Based on Phase Reconstruction Theory and Time Series Data

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  • Guo-Feng Fan

    (School of Mathematics & Statistics Science, Ping Ding Shan University, Ping Ding, China)

  • Meng Han

    (School of Mathematics & Statistics Science, Ping Ding Shan University, Ping Ding, China)

  • Ya-Ting Wang

    (School of Mathematics & Statistics Science, Ping Ding Shan University, Ping Ding, China)

  • Jing-Ru Li

    (School of Mathematics & Statistics Science, Ping Ding Shan University, Ping Ding, China)

Abstract

This article applies a delay method and recursive analysis to reconstruct the phase space to study the evolution mechanism of atmospheric pollution, i.e., air quality monitoring. Based on the theory of chaos, it is proven that there are chaotic characteristics of factors influencing air quality. In the meanwhile, the phase space reconstruction algorithm is employed to map the factors that affect the air quality into the high dimensional space, and then, gives its two-dimensional plane, the chaotic characteristics of each influencing factor are eventually proven. The results of the study not only analyze the evolution mechanism of air pollution in recent years, but also provide a theoretical support for the future of air pollution remediation.

Suggested Citation

  • Guo-Feng Fan & Meng Han & Ya-Ting Wang & Jing-Ru Li, 2017. "Evolution Mechanism of Atmospheric Pollution Based on Phase Reconstruction Theory and Time Series Data," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 8(4), pages 43-52, October.
    • Handle: RePEc:igg:jaec00:v:8:y:2017:i:4:p:43-52
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