An Optimized Grey Dynamic Model for Forecasting the Output of High-Tech Industry in China

Zheng-Xin Wang and Ling-Ling Pei

Mathematical Problems in Engineering, 2014, vol. 2014, 1-7

Abstract:

The grey dynamic model by convolution integral with the first-order derivative of the 1-AGO data and series related, abbreviated as GDMC , performs well in modelling and forecasting of a grey system. To improve the modelling accuracy of GDMC , interpolation coefficients (taken as unknown parameters) are introduced into the background values of the variables. The parameters optimization is formulated as a combinatorial optimization problem and is solved collectively using the particle swarm optimization algorithm. The optimized result has been verified by a case study of the economic output of high-tech industry in China. Comparisons of the obtained modelling results from the optimized GDMC model with the traditional one demonstrate that the optimal algorithm is a good alternative for parameters optimization of the GDMC model. The modelling results can assist the government in developing future policies regarding high-tech industry management.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:586284

DOI: 10.1155/2014/586284

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