Payment Behavior Prediction and Statistical Analysis for Shared Parking Lots
Abstract
As the sharing economy is booming in China, many intelligent shared parking lots appear. Since more and more Chinese households own cars, it is necessary to study the payment behavior of shared parking lots, which may represent the entire sharing economy. In detail, we analyze the factors that influence users’ payment and predict users’ payment behavior of whether and when users will deliver parking bills after parking. We use 29,733 real parking records provided by Huaching Tech, a top smart parking company in China, in our study. After a comprehensive statistical analysis, we use decision tree model to predict users’ payment behavior. Experiments show that the decision tree model can reach 79% accuracy.
Domains
Computer Science [cs]| Origin | Files produced by the author(s) |
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