Application of the Grey and Multi-linear Regression Combined Model in Reverse Logistics Predictions

The accurate prediction of the quantity of reverse logistics is useful to the drafting of industrial development plans and the feasibility research of infrastructure. Taking into account the uncertainties of reverse logistics, this paper uses the two single forecast models, the grey GM (1, 1) and the multi-linear regression models, to model the statistics. Using combination forecast theory, the paper makes predictions based on the prediction effectiveness of the combination forecast model. The results reveal that the accuracy of the combination forecast theory is significantly higher than the two single forecast methods, hence proving the feasibility and effectiveness of the former in predicting the demand for reverse logistics.