Temporally and spatially regular subway passenger clustering and edge detecting method

A passenger and regular technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem of less passenger classification

Active Publication Date: 2014-04-02
深圳市北斗智能科技有限公司
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Benefits of technology

This technology helps analyze passenger behavior by analyzing different types of regular or irregular tickets that may be used for transportation purposes like train cars. It also analyzes how many times they have been served at stations along their route. By doing this it will help identify areas where people tend to frequent them more frequently than others.

Problems solved by technology

The technical problem addressed by this patented study relates to identifying people who consume more than usual amounts of money for everyday activities or purposes (such as commuting). This helps manage costs effectively while also improving overall performance across various modes like road trips, carpool services, train scheduling, airline tickets, and social media platforms.

Method used

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  • Temporally and spatially regular subway passenger clustering and edge detecting method
  • Temporally and spatially regular subway passenger clustering and edge detecting method
  • Temporally and spatially regular subway passenger clustering and edge detecting method

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Embodiment Construction

[0076] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0077] The present invention provides a space-time law subway passenger clustering and edge detection method, which is mainly aimed at passengers with time-space law, that is, passengers with relatively regular travel time and travel locations, such as commuters and students with relatively fixed working hours and work locations. . Spatio-temporal regular subway passenger clustering classifies the spatio-temporal regular passengers with similar characteristics, and the edge detection here is mainly aimed at the category with a relatively small number of passengers. The method provided by the present invention is based on the classification of passengers. When classifying passengers, the passengers are finally divided into 5 categories by analyzing the spatio-temporal characteristics of passengers: Class 1 (passengers who rarely travel...

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Abstract

The invention belongs to the technical field of information data processing, and provides a temporally and spatially regular subway passenger clustering and edge detecting method. The temporally and spatially regular subway passenger clustering and edge detecting method includes steps of S1, acquiring detailed information of temporal-spatial regulation of temporally and spatially regular subway passengers from source data which contain all riding records of the passengers; S2, clustering the temporally and spatially regular subway passengers according to the acquired detailed information of the temporal-spatial regulation; S3, performing edge detection on the clustered temporally and spatially regular subway passengers and analyzing edge features of the clustered temporally and spatially regular subway passengers. The temporally and spatially regular subway passenger clustering and edge detecting method has the advantages that subway passengers are classified on the basis of temporal-spatial data mining, the temporally and spatially regular passengers are clustered according to the quantities of regular time frames of the temporally and spatially regular passengers, and each class of temporally and spatially regular passengers are analyzed and are subjected to edge detection, so that life features of the passengers can be effectively comprehended.

Description

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Claims

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Application Information

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Owner 深圳市北斗智能科技有限公司
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