| Popis: |
The public traffic flow has the gray characteristics of “small sample and poor information”, thereby a forecast method for transfer flow based on the gray soft computing is proposed. This method utilizes the gray system theory to establish gray neural network prediction model, aiming to improve performance of the neural network as well as the accuracy of the system’s prediction by using genetic algorithm. The results show that the optimized model can more accurately predict the traffic flow, providing a more effective way of location selection for public transit transfer hubs. Finally, take the planning of public transit transfer hubs in Lanzhou City as an example to carry out empirical analysis and evaluation for the transfer hubs using this method |
