Prediction of Subway Passenger Flow Based on ARIMA Algorithm
HAI Ling
LIU Wen
LIU Yan
GU Zheng
LIU Zhiyong
Abstract：With the increase in urban population,the outstanding problem is the traffic line transportation soared,leading to the subway of bearing pressure,metro operation dispatching work to bring huge challenges,according to the above problems,it is badly in need of a subway passenger flow prediction method to solve the problem of underground pipe department operation schedul-ing.Based on this,this article in time series method to predict the metro passenger flow,on the basis of quoting the ARIMA model,based on the data analysis,screening,through the analysis of the characteristic changes of subway traffic history data,the data stabili-ty of the 20 sites routes optimization and white noise test,the autocorrelation and partial correlation chart is used to valuation of mod-el parameter,Finally,the fitting degree of ARIMA model is tested to predict the lines of 20 stations and analyze the changes of sub-way passenger flow data,so as to obtain an objective forecast data after simulation calculation,which provides scientific deci-sion-making for the subway operation and dispatching department.
Keywords：data analysispassenger flowARIMA model
Publication Date：2025-03-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 666-670 )