Abstract
Along with the large scale construction of urban rail transit and the application of computer science in the transportation industry, the reasonable, accurate urban rail transit passenger flow prediction has important significance for the line construction benefit analysis, transportation scheme evaluation, passengers monitoring, and emergency response and so on. This paper studies the current integrated prediction method and calculation model system, analyzes the National Day holiday passenger flow data characteristic of Guangzhou Metro Line 5, and proposes a passenger flow prediction method combined the time series model and regression model. And then the results through experiment and demonstration shows that the model can obtain the better forecast precision. This algorithm has strong practical significance for urban rail transit passenger flow short-term and abnormal forecast.
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