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

1
Department of Statistics, Faculty of Science, Sebha University, Sebha, Libya
2
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
Math. Comput. Appl. 2017, 22(1), 21; https://doi.org/10.3390/mca22010021
Received: 28 December 2016 / Revised: 8 February 2017 / Accepted: 8 February 2017 / Published: 22 February 2017
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)
MDPI and ACS Style

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.

AMA Style

Madhi M, Mohamed N. An Initial Condition Optimization Approach for Improving the Prediction Precision of a GM(1,1) Model. Mathematical and Computational Applications. 2017; 22(1):21.

Chicago/Turabian Style

Madhi, Mahdi; Mohamed, Norizan. 2017. "An Initial Condition Optimization Approach for Improving the Prediction Precision of a GM(1,1) Model" Math. Comput. Appl. 22, no. 1: 21.

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