Forecasting the Section Passenger Flow of the Subway Based on Exponential Smoothing

Facing the typical big city is into the network operation ,currently, it brings some difficulties without the section traffic data obtained in real time to monitor and limit measures. To solve the problem, this paper adopts the second exponential smoothing models based on the historical data at the same period, and forecasts the subway section passenger flow. In this paper, the data is collected a section traffic in Beijing Subway from every Monday to every Friday in March 2013, and the former periods are used as the sample data, and predicts the last day, and compares them with the known data to check error. The result shows the method has a strong practical utility.