Public Transit Passenger Transportation Quantity Forecast Based On Synthetic Integrated Multi-Variable Grey Model

The passenger transport system is a multi-level and nonlinear complicated system affected by multi-factors. Grey forecast model to predict urban public transit passenger transportation quantity attracts more attention. Take public transit data of Shijiazhuang city, Hebei province as an example. First, determine the key factors that influence public transit passenger transportation quantity according to the calculation of grey incidence. The region total output value, amount of service bus, urban population, urban road length and service line length are selected. The former two have distinguished incidence, while the latter three are in the same level. In order to avoid information loss caused by giving up the three factors, integrate the three factors of the same incidence level synthetically. Take grey incidence value as weight coefficient to normalize urban population, urban road length and service line length with different magnitude, and then sum up by weight to integrate a synthetic factor. Next, set up MGM (l, n) model to forecast.