Crowd portrait algorithm based on mass bus data

A technology for public transport data and data, applied in structured data retrieval, electronic digital data processing, geographic information database, etc., can solve the problem of lack of urban crowd portrait technology

Active Publication Date: 2021-05-14
HUNAN NORMAL UNIVERSITY
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AI Technical Summary

Problems solved by technology

Traffic data hides the daily behavior of users. When a user group has a similar trajectory, it can be considered that the group has similar char

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  • Crowd portrait algorithm based on mass bus data
  • Crowd portrait algorithm based on mass bus data
  • Crowd portrait algorithm based on mass bus data

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[0069]In order to make the technical problems, technical solutions and advantages to solve the present invention more clearly, and will be described in detail below with reference to the accompanying drawings and specific examples.

[0070]The present invention provides a population portrait algorithm based on massive bus data for existing problems, such asfigure 1 As shown, including the following steps:

[0071]Step S1, data description and pretreatment: Get bus card data and POI (points of interest, point ofinterest) data, and perform pre-processes;

[0072]Step S2, Filter the key area population: Extract the number of travel times by PageRank (a Google Page Ranking Algorithm) algorithm, and the trajectory data of frequent trajectory of the hotspot;

[0073]Step S3, the trajectory textization: obtain the functionality of the coordinates of the passenger according to the POI data, and obtain the text trajectory data of each passenger according to the functionality of the passenger trajectory ...

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Abstract

The invention provides a crowd portrait algorithm based on mass bus data, and the algorithm comprises the following steps: S1, performing data description and preprocessing: obtaining bus card swiping data and POI data, and carrying out the preprocessing; S2, screening crowds in key areas: extracting passenger track data with many travel times and frequent hot spot removal times through a PageRank algorithm; S3, performing track textualization: obtaining the functionality of the coordinates where the passengers are located according to the POI data, and obtaining the text track data of each passenger according to the passenger track data and the functionality of the coordinates where the passengers are located; and S4, performing text clustering: clustering the text trajectory data by adopting a clustering algorithm to obtain a crowd portrait. The method provides data support for multiple application fields such as urban planning and social behavior analysis, facilitates reasonable scheduling and construction of urban resources, and better helps management departments and urban constructors to make optimal decisions for urban construction and development.

Description

technical field [0001] The invention relates to the technical field of crowd portraits, in particular to a crowd portrait algorithm based on massive bus data. Background technique [0002] Modern public transportation technology uses advanced bus card payment system and bus card information database, and records millions of bus travel data every day. The study found that fully mining and utilizing the card swiping data of bus passengers can accurately analyze the daily activities of individuals or groups in the city. These rules can not only effectively help solve the problems of bus route planning and bus company vehicle scheduling in cities, but also provide data support for multiple application fields such as urban planning and social behavior analysis, so as to facilitate the rational scheduling and construction of urban resources and better help Administration and city builders make optimal decisions on city construction and development. [0003] Although the analysis...

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Application Information

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IPC IPC(8): G06F16/335G06F16/35G06F40/216G06F40/30G06F16/29
CPCG06F16/29G06F16/335G06F16/35G06F40/216G06F40/30
Inventor 张锦张建忠魏叶华罗迅娄小平
Owner HUNAN NORMAL UNIVERSITY
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