The Optimization of Grey Model GM (1,1) Based on Posterior Error

In the paper, a new optimization method for the background value of the grey model is proposed based on the posteriori test method of the grey model GM (1,1), and then the initial value is optimized by the least square method. The GM (1,1) model with higher prediction accuracy is obtained, and the application scope of the grey prediction model is extended.