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Received: 2002-09-03

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Journal of Zhejiang University SCIENCE A 2003 Vol.4 No.5 P.578~583


Application of uncertainty reasoning based on cloud model in time series prediction

Author(s):  ZHANG Jin-chun, HU Gu-yu

Affiliation(s):  Institute of Command Automation, PLA University of Science and Technology, Nanjing 210007, China

Corresponding email(s):   jinchunzhang@sina.com.cn

Key Words:  Time series prediction, Cloud model, Simple exponential smoothing method

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ZHANG Jin-chun, HU Gu-yu. Application of uncertainty reasoning based on cloud model in time series prediction[J]. Journal of Zhejiang University Science A, 2003, 4(5): 578~583.

@article{title="Application of uncertainty reasoning based on cloud model in time series prediction",
author="ZHANG Jin-chun, HU Gu-yu",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

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%T Application of uncertainty reasoning based on cloud model in time series prediction
%A ZHANG Jin-chun
%A HU Gu-yu
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%@ 1869-1951
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2003.0578

T1 - Application of uncertainty reasoning based on cloud model in time series prediction
A1 - ZHANG Jin-chun
A1 - HU Gu-yu
J0 - Journal of Zhejiang University Science A
VL - 4
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SP - 578
EP - 583
%@ 1869-1951
Y1 - 2003
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2003.0578

time series prediction has been successfully used in several application areas, such as meteorological forecasting, market prediction, network traffic forecasting, etc., and a number of techniques have been developed for modeling and predicting time series. In the traditional exponential smoothing method, a fixed weight is assigned to data history, and the trend changes of time series are ignored. In this paper, an uncertainty reasoning method, based on cloud model, is employed in time series prediction, which uses cloud logic controller to adjust the smoothing coefficient of the simple exponential smoothing method dynamically to fit the current trend of the time series. The validity of this solution was proved by experiments on various data sets.

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