Key Points of Railway Police Work based on Bayesian Passenger Flow Forecast Method under the Normalization of COVID-19 Prevention and Control

Abstract

China has entered the stage of normalized COVID-19 prevention and control, but the pressure of
overseas COVID-19 input continues to increase, and the railway COVID-19 prevention and
control police work is still facing a major test. This paper analyzes the characteristics of railway
passenger flow under the influence of the COVID-19 situation, establishes a passenger flow
forecasting method based on Bayesian theory, and puts forward the key points of railway police
work by improving the police mode, strengthening daily police, optimizing smart policing,
relying on mass prevention and mass treatment, It provides a theoretical reference for the railway
public security organs to effectively control the public health risks and social security risks under
the normalization of COVID-19 prevention and control, effectively maintain the railway
operation order, and strive to ensure the safe travel of passengers.