New Proposal and Accuracy Evaluation of Grey Prediction GM

Guo-Dong LI; Daisuke YAMAGUCHI; Kozo MIZUTANI; Masatake NAGAI

doi:10.1093/ietfec/e90-a.6.1188

New Proposal and Accuracy Evaluation of Grey Prediction GM

Guo-Dong LI, Daisuke YAMAGUCHI, Kozo MIZUTANI, Masatake NAGAI

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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.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E90-A No.6 pp.1188-1197

Publication Date: 2007/06/01

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Online ISSN: 1745-1337

DOI: 10.1093/ietfec/e90-a.6.1188

Type of Manuscript: PAPER

Category: Information Theory

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Guo-Dong LI, Daisuke YAMAGUCHI, Kozo MIZUTANI, Masatake NAGAI, "New Proposal and Accuracy Evaluation of Grey Prediction GM" in IEICE TRANSACTIONS on Fundamentals, vol. E90-A, no. 6, pp. 1188-1197, June 2007, doi: 10.1093/ietfec/e90-a.6.1188.
Abstract: 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.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e90-a.6.1188/_p

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@ARTICLE{e90-a_6_1188,
author={Guo-Dong LI, Daisuke YAMAGUCHI, Kozo MIZUTANI, Masatake NAGAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={New Proposal and Accuracy Evaluation of Grey Prediction GM},
year={2007},
volume={E90-A},
number={6},
pages={1188-1197},
abstract={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.},
keywords={},
doi={10.1093/ietfec/e90-a.6.1188},
ISSN={1745-1337},
month={June},}

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TY - JOUR
TI - New Proposal and Accuracy Evaluation of Grey Prediction GM
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1188
EP - 1197
AU - Guo-Dong LI
AU - Daisuke YAMAGUCHI
AU - Kozo MIZUTANI
AU - Masatake NAGAI
PY - 2007
DO - 10.1093/ietfec/e90-a.6.1188
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E90-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2007
AB - 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.
ER -