Passenger risk level classification method and device, electronic equipment and storage medium

Abstract

The invention provides a passenger risk level classification method and device, electronic equipment and a storage medium; a PSOBP neural network model used for dividing passenger risk levels is trained in advance, and when passenger risk level classification needs to be carried out on passengers to be inspected, a task thread is extracted through awakening, and a data extraction module is calledto establish connection with a source data platform; the method also includes extracting index data information of the to-be-inspected passenger, and performing data integration and processing on theindex data information of the to-be-inspected passenger to obtain a quantitative value corresponding to the index data information of the to-be-inspected passenger; and determining the risk level of the passenger to be inspected by using the PSOBP neural network model according to the quantitative value corresponding to the index data information of the passenger to be inspected. According to theembodiment of the invention, security check resources can be scientifically configured, the security check pressure is relieved while the security level is guaranteed, the queuing waiting time of passengers is shortened, the airport service quality and the passenger satisfaction are improved, and finally, the purpose of high-quality development of the civil aviation industry is achieved.

Description

technical field [0001] The present invention relates to the technical field of civil aviation, and more specifically, relates to a passenger risk level classification method, device, electronic equipment and storage medium. Background technique [0002] With the rapid development of the civil aviation industry, the throughput of airport passengers has gradually increased, and the structure of civil aviation passengers has also become diversified. However, the traditional security inspection system has not made corresponding changes, resulting in increased passenger security inspection queuing time, reduced inspection efficiency and inspection quality, and increased work intensity of security personnel. The traditional security inspection system has been unable to meet the current airport and passenger requirements for security inspection efficiency. need. [0003] In recent years, domestic and foreign studies have begun to evaluate passenger risk levels and tried to use the...

AI Technical Summary

Problems solved by technology

However, the traditional security inspection system has not made corresponding changes, resulting in increased passenger security inspection queuing time, reduced inspection efficiency and inspection quality, and increased work intensity of security personnel. The traditional security inspection system has been unable to meet the current airport and passenger requirements for security inspection efficiency. need

[0003] In recent years, domestic and foreign studies have begun to evaluate passenger risk levels and tried to use them in airports. For example, during the 1960s and 1970s, FAA (Federal Aviation Administration, US Federal Aviation Administration) funded and supported the development of CAPPS (Computer Assisted Passenger Prescreening System, Computer Aided Passenger Pre-screening System), however, the watch list of high-risk passengers provided cannot be updated in real time, and the database of tourism and other industries cannot be used to investigate the pre-boarding behavior of passengers on the watch list, resulting in the inability to accurately identify all possib

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