Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

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
View PDF7 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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 characteristics. This feature is the group portrait of the group. However, there are relatively few technologies for studying urban crowd portraits.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Crowd portrait algorithm based on mass bus data
  • Crowd portrait algorithm based on mass bus data
  • Crowd portrait algorithm based on mass bus data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0069] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will describe in detail with reference to the drawings and specific embodiments.

[0070] Aiming at the existing problems, the present invention provides a crowd portrait algorithm based on massive bus data, such as figure 1 shown, including the following steps:

[0071] Step S1, data description and preprocessing: obtain bus card swiping data and POI (Point of Interest) data, and perform preprocessing;

[0072] Step S2, screening crowds in key areas: extracting passenger track data with frequent travel times and frequent trips to hotspot areas through the PageRank (a google web page ranking algorithm) algorithm;

[0073] Step S3, Trajectory Textization: According to the POI data, the functionality of the passenger's coordinates is obtained, and according to the passenger trajectory data and the functionality of the passenger's coordi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

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...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com