Research on the Prediction of Urban Passenger Transport based on Support Vector Machine

Abstract

The prediction model of urban passenger transport is proposed in this paper, which can provide the theoretical foundation for the government management to make decision and to predict passenger volume of urban transport accurately. The prediction model of urban passenger transport is established by using support vector machine (SVM), combining with the volume of the urban of passenger transport in Xi'an over years. The prediction model of urban passenger transport is validated, and the simulation results indicate that this prediction model is effective. Besides it has stronger fitting than the prediction based on BP neural network.