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Multivariable Forecasting Model Based on Trend Grey Correlation Degree and its Application

In: The 19th International Conference on Industrial Engineering and Engineering Management

Author

Listed:
  • Li-ping Fu

    (Public Resource Management Research Center, Tianjin University)

  • Lu-yu Wang

    (Public Resource Management Research Center, Tianjin University)

  • Juan Han

    (Tianjin University)

Abstract

Among the current forecasting methods, trend grey correlation degree forecasting method is limited to a single variable time series data, but cannot solve the problem of multivariable forecasting. While multiple regression forecasting can only be used for multivariable linear forecasting, and can be easily affected by random factors. Therefore, this paper combines trend grey correlation degree forecasting based on optimization method and the multiple regression forecasting, generates the multivariable forecasting model based on trend grey correlation analysis, and uses this model to forecast GDP in Henan Province, not only to overcome the effect of random factors on time series, but also to comprehensively consider the various factors that affect the development of objects, thus to achieve the effect of improving accuracy and increasing the reliability of forecasting. And this paper also provides a new method for the study of multivariable combination forecasting.

Suggested Citation

  • Li-ping Fu & Lu-yu Wang & Juan Han, 2013. "Multivariable Forecasting Model Based on Trend Grey Correlation Degree and its Application," Springer Books, in: Ershi Qi & Jiang Shen & Runliang Dou (ed.), The 19th International Conference on Industrial Engineering and Engineering Management, edition 127, chapter 0, pages 403-410, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-38391-5_41
    DOI: 10.1007/978-3-642-38391-5_41
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