Data processing method, device, equipment and medium

Abstract

The embodiment of the present invention discloses a data processing method, device, equipment and medium. The data processing method includes: performing grid processing on the target area according to the digital map information of the target area to obtain S grid areas of equal area , S is an integer greater than or equal to 1; according to the position data of the target area acquired by the base station in the preset first time period, determine the amount of moving points in each grid area; for all grids in the preset first time period The fragment moving point amount missing in the grid area is complemented to obtain the complete moving point amount of the target area. The fragment moving point amount is the moving point amount of a grid area within a preset time length, and the preset time length is A time period within the first time period is set.

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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