Passenger flow prediction and application of Beijing subway Changping Line based on grey model
The grey GM(1,1)and Verhulst models can overcome the disadvantage of less historical data in rail transit passenger flow prediction.Through calculation,it is found that the predicted result of GM(1,1)model is 3.04%smaller than the true value.The predicted result of Verhulst model is 1.78%larger than the true value.By using the coefficient of variation method to determine the weight,the two models are improved,and the predicted value is 0.734%smaller than the true value,which is better than GM(1,1)model 2.31%and Verhulst model 2.52%,which is conducive to the improvement of the accuracy of prediction results.The application of grey forecasting method can help the rail transit operators to improve the line capacity,predict the passenger flow pressure of the station,and provide decision-making basis for the layout of commercial outlets.
grey GM(1,1)grey Verhulstcoefficient of variation methodpassenger flow prediction
NETL
NSTL
万方数据
