Freight and Passenger Volume Prediction using Multiple Regression

Abstract

This paper analyzes the influencing factors of highway passenger and freight traffic, determines its influencing factors, and collects relevant statistical data from 117 different regions. Based on the principle of multiple linear regression method, first all variables are incorporated into the multiple regression equation for simulation. Second, integrate, demonstrate the applicability of the model, and then use the stepwise multiple regression method for model fitting. Based on this idea, the multiple linear regression model is constructed and forecasted for the highway passenger and freight volume. The results show that the stepwise multiple regression is effective. While the number of variables is greatly reduced and the calculation process is simplified, the model's fit is still good, and the problem of collinear between multiple variables is solved, and the regression coefficient of the variable is not consistent with the actual problem, and the result is predicted, It is also consistent with the actual situation and the applicability of the verification method, which can provide application references for road passenger and freight volume forecasting in other related areas.