Short-Term Passenger Flow Forecasting Method Based on Multi-Model Combination

Abstract

With the rapid economical development, subway brings people a high-speed and convenient way to travel. But with the increasing complexity of subway lines and the increase of passenger flow, it brings great pressure to the commissioning and management of subway operation. In order to alleviate the pressure of metro traffic. It is very significant to prognosis passenger flow. This paper constructs a combined model of LSTM and ARIMA to predict the passenger flow data of Metro Line 1 in a city. The final experimental results show that the integration of the two models is more conducive to prognosis the short-term passenger flow of the metro.