Adaptive and high-precision grey forecasting model

Although the grey forecasting model has been successfully employed in various fields and demonstrated promising results, literatures show its performance still could be improved. Therefore, a new model named EFGMm(1, 1) is proposed in this paper by eliminating the error term resulted from the traditional calculation of background value with an integration equation to substitute for such error term. In addition, Fourier series and exponential smooth technique have also been integrated into the new model to reduce the periodic and stochastic residual errors, respectively. An illustrative example of building material stock index is adopted for demonstration. Results show that the proposed model can increase the prediction accuracy, particularly when the system is instable.