Logistic Forecast Analysis of Sichuan Province on the Basis of Multi-model Combination
DOI:
https://doi.org/10.54691/bcpbm.v34i.3083Keywords:
Logistics forecast; freight turnover; Sichuan province; combined prediction model.Abstract
Sichuan province serving as the hub of comprehensive transportation in the southwest of our country, has the longest transportation lines in China and its freight transportation maintains a healthy development. In order to give a quantitative reference for the government to formulate logistics improvement and development policies, determining the scale of logistics infrastructure construction and analyzing the situation of the logistics market, this paper establishes several forecasting models to reveal the mechanism and forecast the logistics demand. Freight turnover is used as an indicator to reveal logistics demand and seven variables are summarized as influential factors. Then, multiple regression model, BP neural network model and grey forecasting model are available ways to do the forecast and their forecasting error is measured by several criterions. In order to avoid the technical shortage of a single model, this paper give each of the model a weight ratio and use a combination model to analyze the logistics demand of Sichuan Province. Since the multi-model has low overall error rate, using this combination model to predict the logistics needs of Sichuan in the coming years is pretty feasible.
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