A proposal for a predictive analysis model for bike-sharing systems based on a mixed model of statistical and machine-learning approaches.

The model assumes a Poisson distribution on bike station arrival and departures.

The model is validated by comparing the predicted arrival and departure rates to the actual rates.

The case study results show that our model can outperform other naïve approaches using the mean on arrival and departure rates.