Development of the regional freight transportation demand prediction models based on the regression analysis methods

Different prediction models based on the regression analysis methods are studied in this work and they are successfully implemented for predicting the regional freight transportation demand (RFTD). RFTD plays an important role in reflecting the economic states, such as production improvement, economic restructuring, and economic growth style. Thus, the prediction models for RFTD have been widely used in many areas, such as academic and industrial domains. In this work, based on different prediction models, several Regional Freight Transportation Demand Prediction Models (RFTDPMs) have been constructed by using Multiple Linear Regression (MLR), Non-Linear Regression (NLR), and Simple Linear Regression (SLR). According to the fitting efficiency, the simulation results show that the RFTDPM based on NLR offers superior performances in predicting RFTD compared with the other regression models. However, if the validation rates of the RFTDPMs are taken into consideration, the SLR based model outperforms the other two prediction models.