High-speed rail user identification method, device, equipment and medium

Abstract

Disclosed is a high-speed rail user identification method, device, equipment, and medium, the method comprising: performing cluster analysis on a set of speed-distance association pairs of high-speed rail private network users on a preset high-speed rail private network cell switching chain to obtain multiple clusters, The speed-distance association pair is an association pair composed of the average speed between two private network cells on the predetermined high-speed rail line and the line distance between the two private network cells; based on the respective minimum speeds of multiple clusters, Determining the speed threshold; determining the average speed of the user to be identified between two user signaling occurrence cells, the user signaling occurrence cell is the cell where the user signaling of the user to be identified on the preset high-speed rail private network cell handover chain occurs; and in If the average speed of the user to be identified is greater than the speed threshold, it is determined that the user to be identified is a high-speed rail user. Therefore, a reasonable speed threshold and user average speed are determined through clustering to accurately identify high-speed rail users.

Description

technical field [0001] The present invention relates to the field of wireless communication technology, in particular to a high-speed rail user method, device, equipment and medium Background technique [0002] In recent years, with the rapid development of high-speed rail construction, high-speed rail has become a travel choice for more and more users. The signaling data of high-speed rail users can provide data support for upper-level applications to analyze line passenger flow, station passenger flow, OD analysis of passenger travel patterns, and high-speed rail commuter passenger identification. [0003] The existing high-speed rail user identification algorithm based on mobile signaling can be summarized as follows: filter out users who meet the following three conditions at the same time: a. user signaling appears in the high-speed rail private network; b. user location trajectory matches the high-speed rail line; c. The user is moving faster than a certain threshold....

AI Technical Summary

Problems solved by technology

[0004] Existing algorithms identify high-speed rail users by matching multiple consecutive cells in the handover chain, which may easily cause missed identification of high-speed rail users

The existing algorithm calculates the user's moving speed based on the time difference between the line distance between the cells that appear successively in user signaling and the line mapping time point. The error is large, which may easily cause high-speed rail user misidentification.

Moreover, the existing algorithm does not consider the time of passengers waiting and staying in the station when calculating the user's moving distance, resulting in the calculated moving speed being lower than the actual speed, resulting in missed identification of high-speed rail users

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