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Math. Comput. Appl. 2017, 22(1), 21;

An Initial Condition Optimization Approach for Improving the Prediction Precision of a GM(1,1) Model

Department of Statistics, Faculty of Science, Sebha University, Sebha, Libya
School of Informatics and Applied Mathematics, University Malaysia Terengganu (UMT), Kuala Terengganu 21300, Terengganu, Malaysia
Author to whom correspondence should be addressed.
Academic Editor: Fazal M. Mahomed
Received: 28 December 2016 / Revised: 8 February 2017 / Accepted: 8 February 2017 / Published: 22 February 2017
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Grey model GM(1,1) has attained excellent prediction accuracy with restricted data and has been broadly utilized in a range of areas. However, the GM(1,1) forecasting model sometimes yields large forecasting errors which directlyaffect the simulation and prediction precision directly. Therefore, the improvement of the GM(1,1) model is an essential issue, and the current study aims to enhance the prediction precision of the GM(1,1) model. Specifically, in order to improve the prediction precision of GM(1,1) model, it is necessary to consider improving the initial condition in the response function of the model. Consequently, the purpose of this paper is to put forward a new method to enhance the performance of the GM(1,1) model by optimizing its initial condition. The minimum sum of squared error was used to optimize the new initial condition of the model. The numerical outcomes show that the improved GM(1,1) model provides considerably better performance than traditional grey model GM(1,1) . The result demonstrates that the improved grey model GM(1,1) achieves the objective of minimizing the forecast errors. View Full-Text
Keywords: GM(1,1) model; initial condition; prediction precision of GM(1,1) GM(1,1) model; initial condition; prediction precision of GM(1,1)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Madhi, M.; Mohamed, N. An Initial Condition Optimization Approach for Improving the Prediction Precision of a GM(1,1) Model. Math. Comput. Appl. 2017, 22, 21.

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