关键词: 离散GM(1,1)模型，渐消记忆，递推算法，预测

Abstract: Considering the different effects of the old and new data on the prediction results, an improved moving-aver- age pretreatment method was established for the original data. On this basis,the forgetting factor was introduced to set different weight for the old and new data, and then the fading memory discrete GM(1，1) model was proposed. ho han- dle with the huge calculational burden of GM(1，1) model,a new online real-time recursive prediction algorithm of the fading memory discrete grey model was presented. The proposed model and recursive algorithm were employed to pre- diet the traffic accidents and the region freight Ton-kilometers. The results show that the real-time tracking ability is enhanced and the prediction precision is improved while solving inverse matrix is avoided.

Key words: Discrete GM(1，1) model, Fading memory, Recursive algorithm, Forecast