Abstract

The Nash nonlinear grey Bernoulli model (NNGBM(1,1)) is a flexible grey system model that can be used to forecast nonlinear data. In order to better forecast the fluctuations contained in the original data, a Fourier Nash nonlinear grey Bernoulli model (FNNGBM(1,1)) is proposed in this research. The parameters optimization of FNNGBM(1,1) is formulated as a combinatorial optimization problem and is solved collectively using the concept of Nash equilibrium. The simulation and practical application to fluctuation data both prove that FNNGBM(1,1) could offer a more precise forecast than NNGBM(1,1) and the Fourier residual GM(1,1) (FGM(1,1)). Thus, FNNGBM(1,1) is selected to forecast the export, import, trade balance and trade specialization coefficient of Chinese high-tech products during the period 2012 to 2014. The forecasting results show that import/export data will maintain rapid growth, with corresponding trade balance enlargement; however, there will be a concomitant decrease in the trade specialization coefficient.

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