Usage Behavior Analysis of Intelligent Network based Public Bicycle Rental System
Hao-En Chueh, Chang-Yi Kao, Meng-Luen Wu · 2020
Many modern cities have their public bicycle rental systems. The bicycle rental system does not only provide convenience for short distance traveling but also gives an opportunity for the predictions of people in the city, and brings efficiency for government as well as enterprises. Some bicycle rental systems are connected to the Internet and the rental status of each bicycles are available, and huge amount of data are produced every day for analysis. In this research, several data mining approaches including the data processing, feature selection, frequent pattern mining are used to predict user behaviors. The data are cleaned and clustered for more accurate analysis. The processed data can be used to extract frequent patterns and built decision tree of user behaviors. According to the method proposed in this research, a full scheme for the public bicycle rental system is provided to make better strategies for government and commercial use.