Abstract
Bicycle-sharing systems are a new type of transportation service that provides bicycles for shared use; they allow users to rent a bicycle at one station, ride it, and return it to another station in the same city. In this paper the author, the trip data of Shanghai Mobike in August 2016 are taken as the main raw data, and the trip characteristics of shared bicycle system are deeply studied by using data mining method, and the ARIMA model is used to predict bicycle trip. Finally, RMSE is used to judge the prediction accuracy. The results show that the model can effectively predict the residents’ trip, and the prediction accuracy is high, which can provide a certain reference for residents’ trip.
