Short Term Forecasting of ofo Traffic Flow Based on Grey Theory
ZHAO Guangyuan
SHANG Qiuyan
Abstract：With the rapid development of shared bike(ofo),it is very important to study its short-term demand forecasting. According to the grey theory,the characteristics of GM(1,1)model are analyzed,and it is found that GM(1,1)model is applica?ble to monotone sequences with strong exponential law. Considering the short-term traffic flow data in a certain period of volatility and saturation,in order to improve the precision and efficiency of short-term prediction model,Grey Markov model is combined based on GM(1,1)model. Using ofo data from September 1,2017 to September 8th,the Matlab software toolbox is used to validate the model by computer simulation through theoretical analysis and simulation prove the feasibility and practicability of the scheme. The combination model has strong data approximation ability,effectively improves the operational accuracy and efficiency of the al?gorithm,and can be used in the prediction of vehicle flow fluctuation or saturation stage.
Keywords：Grey theoryGrey Markov modelofo vehicle flowshort-term prediction
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1586-1590,1612 )