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Nonlinear Time Series Prediction of Atmospheric Visibility in Shanghai

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Time Series Analysis, Modeling and Applications

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 47))

Abstract

Atmospheric visibility has recently become more essential to both the aviation safety and environmental pollution studies. Due to the characteristic of nonlinear time series, the visibility is difficult to predict by traditional statistical method. In this study, fuzzy time series models are used to predict the atmospheric visibility in Shanghai. The irregular dynamic of visibility was firstly investigated by the histogram as well as the autocorrelation analysis to identify the long-term memory of its behavior. Observed single-variable time series data were used to construct the fuzzy forecasting model. Parameters needed to construct the model were chosen to extract the rule of visibility variation. The results revealed that fuzzy time series could well predict the variation of visibility. The relative error between model outputs and observations was within the practically acceptable limits, which points out that atmospheric visibility could be explained and well predicted by the fuzzy time series.

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Authors and Affiliations

  1. Key Laboratory of Nuclear Analysis Techniques, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai, 201800, China

    Jian Yao & Wei Liu

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  1. Jian Yao
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  2. Wei Liu
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Correspondence to Jian Yao .

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Editors and Affiliations

  1. , Electrical & Computer Engineering, University of Alberta, 9107 - 116 Street, 2nd Floor, ECERF, Edmonton, T6G 2V4, Canada

    Witold Pedrycz

  2. , Graduate Institute of Educational Measur, National Taichung University of Educatio, Administration Building A110, Taichung, Taiwan R.O.C.

    Shyi-Ming Chen

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Yao, J., Liu, W. (2013). Nonlinear Time Series Prediction of Atmospheric Visibility in Shanghai. In: Pedrycz, W., Chen, SM. (eds) Time Series Analysis, Modeling and Applications. Intelligent Systems Reference Library, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33439-9_18

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  • DOI: https://doi.org/10.1007/978-3-642-33439-9_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33438-2

  • Online ISBN: 978-3-642-33439-9

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