Passenger Traffic Forecast Based on Unbiased Grey Markov Model
MA Biao
Abstract：In order to make the plan of urban rail transit train more reasonable, the paper provides scientific basis for arranging police force by the public security organ of urban rail transit, and studies the method of passenger flow forecast. According to the analysis of the basic characteristics of the grey GM (1, 1) model and the unbiased grey GM (1, 1) model, the Markov model is established. On the basis of the daily passenger flow from February 3 to February 18 of 2017 in Zhengzhou subway line 1, the GM (1, 1) model and the Markov model are used to calculate the passenger flow, and the forecast results are tested and compared. The results show that the Markov model improves the prediction accuracy of passenger traffic by 54％ compared with the unbiased grey model. The Markov model is used to forecast the traffic volume of the future 3D, which accords with the changing characteristics of urban rail transit passenger flow.
Keywords：grey theorymodel testMarkov modelpassenger forecasting
Publication Date：2018-01-01
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：8( 35-41,73 )