Multiple Variables Time Series Adaptive Prediction Model Based on Grey Theory

Xiao Lei Li; Jie Zhong Ma; Yang Ming Guo

doi:10.4028/www.scientific.net/AEF.6-7.97

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HomeAdvanced Engineering ForumAdvanced Engineering Forum Vols. 6-7Multiple Variables Time Series Adaptive Prediction...

Multiple Variables Time Series Adaptive Prediction Model Based on Grey Theory

Abstract:

Fault prediction is critical to ensure the safety and reliability of complex system. The reported fault prediction methods have achieved some success in practical applications. Generally, the information used in fault prediction is always mined from multi-variable time series and small simple data. Thus, based on grey prediction theory, an adaptive prediction model with multi-variable small simple time series data is proposed. In this method, after analyzing the disadvantages of model, we modify the initial values and background values of model, and then the interrelations and characteristics of the multiple variables time series are taken into account. The results of experiment with a certain complex system show that the model has good prediction precision, which will be useful in applications.

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Periodical:

Advanced Engineering Forum (Volumes 6-7)

Pages:

97-103

DOI:

https://doi.org/10.4028/www.scientific.net/AEF.6-7.97

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Online since:

September 2012

Authors:

Xiao Lei Li, Jie Zhong Ma, Yang Ming Guo

Keywords:

Grey Prediction, Multi-Variable Time Series, Prediction Model

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Creative Commons CC BY 4.0

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