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Meteorology and Atmospheric Physics

, Volume 50, Issue 4, pp 231–236 | Cite as

An application of chaotic theory in long range forecasts

  • Zhen-Shan Lin
  • Shi-Da Liu
Article

Summary

In this paper we combine chaotic theory with statistics to present three forecast models: a model of equal distance ind-dimensional phase space, a mode regression model of twelve units and a model of neighborhood model regression. Many experiments show that all these models can generate accurate forcasts.

Keywords

Climate Change Waste Water Model Regression Regression Model Water Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Farmer, J. D., Sidorwich, J. J., 1987: Predicting chaotic time series.Phys. Rev. Letters,50, 845–849.Google Scholar
  2. Grassberger, P., Procaccia, I., 1983: Characterization of strange attractors.Phys. Rev. Letters,50, 346–349.Google Scholar
  3. Lin, Z. S., 1991: The phase space models for the longterm forecasting. Ph.D. Dissertation, Peking University.Google Scholar

Copyright information

© Springer-Verlag 1992

Authors and Affiliations

  • Zhen-Shan Lin
    • 1
  • Shi-Da Liu
    • 2
  1. 1.Department of Atmospheric ScienceNanjing UniversityNanjingPeoples Republic of China
  2. 2.Department of GeophysicsPeking UniversityBeijingPeoples Republic of China

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