A Passenger Flow Prediction Method for Bus Lines Based on Multiple Stepwise Regression Analysis

Abstract

Accurate bus passenger flow prediction can provide effective data support for bus operators to realize intelligent bus scheduling and scientific bus network planning. This paper collects the relevant data of bus routes in a city in 2020, uses the Person correlation coefficient to select the eigenvalue, defines the sample similarity, selects the training data based on the similarity, establishes the multiple stepwise regression model, and uses the established model to predict the adjusted routes. The experiment shows that the established regression model is suitable for the prediction of bus passenger flow.

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