Optimized GM(1,1) power model and its application.

As to the optimization of the power exponent and background value in the GM(1,1) power model, this paper summarizes the modeling steps and disadvantages of the traditional method. Two non-linear optimization models are constructed with the objective of minimum average relative error, the constraints of relationships between parameters in order to optimize the power exponent and the background value. The results show that the optimized models make the absolute value of the average relative error smallest in theory. The new method has solved the problem of the inconsistency in grey model testing. Finally, we illustrated the superiority and effectiveness of the new methods with the example of simulating and forecasting the promotion rates from senior secondary schools to higher education in China. [ABSTRACT FROM AUTHOR]