Data processing method, device, equipment and medium

Abstract

The embodiment of the invention discloses a data processing method and device, equipment and a medium. The method comprises the following steps: carrying out the rasterization of a target region according to the digital map information of the target region, obtaining S grid regions with the same area, and S is an integer greater than or equal to 1; determining the moving point quantity of each grid region according to the position data of the target region obtained by the base station in the preset first time period; complementing the missing fragment movement point quantities of all the gridregions in the preset first time period to obtain a complete movement point quantity of the target region, the fragment movement point quantity being a movement point quantity of one grid region in apreset duration, and the preset duration being a time period in the preset first time period.

Description

technical field [0001] The present invention relates to the field of wireless communication, in particular to a data processing method, device, equipment and medium. Background technique [0002] With the advent of the 4G network (the 4Generation mobile communication technology) era, wireless networks provide more means and methods for discovering and analyzing crowd gatherings. The measurement report (Measurement Report, MR) data mainly comes from the physical layer of the user (UE) and the base station (eNodeB), which can accurately locate the location of the mobile phone user, and can better monitor the gathering status of the crowd by analyzing the collected MR data. [0003] However, in order to ensure the use of 4G signals by users, MR data generally adopts a sampling reporting mode, and the uncertainty of sampling time and space results in serious lack of MR data, and it is difficult to directly use MR data to estimate the changes in crowd gathering throughout the day...

AI Technical Summary

Problems solved by technology

[0003] However, in order to ensure the use of 4G signals by users, the MR data generally adopts the sampling reporting mode, and the uncertainty of sampling time and space results in a serious lack of MR data, and it is difficult to directly use MR data to estimate the changes in crowd gathering throughout the day

[0004] At present, the commonly used missing data processing methods include linear regression imputation method, ratio imputation method and attribution completion method, etc., but these methods are relatively ineffective in completing missing data.

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