NDLI: Application of Grey Relational Analysis for Multivariate Time Series

Content Provider	IEEE Xplore Digital Library
Author	Sallehuddin, R. Shamsuddin, S.M.H. Hashim, S.Z.M.
Copyright Year	2008
Description	Author affiliation: Fakulti Sains Komputer dan Sistem Maklumat, Univ. Teknol. Malaysia, Skudai (Sallehuddin, R.; Shamsuddin, S.M.H.; Hashim, S.Z.M.)
Abstract	Grey relational analysis (GRA) has been widely applied in analysing multivariate time series data (MTS). It is an alternate solution to the traditional statistical limitations. GRA is employed to search for grey relational grade (GRG) which can be used to describe the relationships between the data attributes and to determine the important factors that significantly influence some defined objectives. This paper demonstrates how GRA has been successfully used in identifying the significant factors that affect the grain crop yield in China from 1990 to 2003. The results from analysing the sample data revealed that the main factor that affects the trend of crop yield is the consumption of pesticide and chemical fertilizer and the least important factor to be considered is the agricultural labour. Thus, by properly adjusting the significant affecting factors, the China's crop yield performance can be further improved. Furthermore, GRA can provide a ranking scheme that gives the order of the grey relationship among the dependent and independent factors which leads to essential information such as which input factor need to be considered to forecast grain crop yield more precisely when using artificial neural network (ANN). In order to evaluate the performance of GRA in ANN model, a comparison is made using multiple linear regression (MR) statistical method. The results from the experiment show that ANN using GRA has outperformed the MR model with 99.0% in forecasting accuracy.
Starting Page	432
Ending Page	437
File Size	233961
Page Count	6
File Format	PDF
ISBN	9780769533827
DOI	10.1109/ISDA.2008.181
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-11-26
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Grey Relational Grade Data analysis Statistical analysis Chemical analysis Time series analysis Linear regression Crops Artificial neural networks Predictive models Regression analysis Multiple Linear Regression Artificial Neural Network Grey Relational Analysis Economic forecasting Multivariate
Content Type	Text
Resource Type	Article

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