NDLI: The interval forecasting method based on non-equidistant GM(1,1) with application to regional grain production

Content Provider	IEEE Xplore Digital Library
Author	Li Bing-jun He Chun-hua
Copyright Year	2009
Description	Author affiliation: College of Information and Management Science, Henan Agricultural University, Zhengzhou, 450002, China (Li Bing-jun; He Chun-hua)
Abstract	Based on a raw sequence with some aberrant data, it is difficult for any prediction technique to give out an accurate point forecasting value. However, an interval forecasting value obtained by one or more different techniques should be reasonable and acceptable. In this paper, a data sequence having a linear tendency with upper/positive and lower/negative aberrances is analyzed. Upon the linear regression analysis, the data sequence is classified into three parts: upper/positive aberrant data, lower/negative aberrant data and normal data. Then introducing the non-equidistant GM(1,1), we establish three models : a non-equidistant GM(1,1) based on upper aberrant data, a non-equidistant GM(1,1) based on lower aberrant data and a linear regression model based on the remaining normal data. Using the established models, we can obtain three prediction intervals. Applying it to the prediction of regional grain production, we demonstrate the good performance and effectiveness of the proposed prediction method.
Starting Page	543
Ending Page	548
File Size	94980
Page Count	6
File Format	PDF
ISBN	9781424449149
DOI	10.1109/GSIS.2009.5408252
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-11-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Production systems Data analysis Biological system modeling Linear regression Prediction methods Predictive models Educational institutions Information management Helium Intelligent systems
Content Type	Text
Resource Type	Article

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