New Proposal and Accuracy Evaluation of Grey Prediction GM

Guo-Dong LI  Daisuke YAMAGUCHI  Kozo MIZUTANI  Masatake NAGAI  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E90-A   No.6   pp.1188-1197
Publication Date: 2007/06/01
Online ISSN: 1745-1337
DOI: 10.1093/ietfec/e90-a.6.1188
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Information Theory
grey theory,  grey model (GM),  cubic spline function,  Taylor approximation method,  

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Grey model (abbreviated as GM), which is based on Deng's grey theory, has been established as a prediction model. At present, it has been widely applied in many research fields to solve efficiently the predicted problems of uncertainty systems. However, this model has irrational problems concerning the calculation of derivative and background value z since the predicted accuracy of GM is unsatisfying when original data shows great randomness. In particular, the predicted accuracy falls in case of higher-order derivative or multivariate greatly. In this paper, the new calculation methods of derivative and background value z are first proposed to enhance the predicted power according to cubic spline function. The newly generated model is defined as 3spGM. To further improve predicted accuracy, Taylor approximation method is then applied to 3spGM model. We call the improved version as T-3spGM. Finally, the effectiveness of the proposed model is validated with three real cases.