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Airport aviation passenger classification and identification method based on mobile phone signaling data

A mobile phone signaling, classification and identification technology, applied in the field of big data computing, can solve the problems of discontinuous behavior trajectory, few samples of air passenger travel behavior information, and poor timeliness.

Pending Publication Date: 2020-09-11
HEBEI NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the air passenger travel behavior information obtained by the above methods has shortcomings such as small samples, poor timeliness, and discontinuous behavior trajectories.

Method used

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  • Airport aviation passenger classification and identification method based on mobile phone signaling data
  • Airport aviation passenger classification and identification method based on mobile phone signaling data
  • Airport aviation passenger classification and identification method based on mobile phone signaling data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0040] Such as figure 1 As shown, the airport air passenger classification and recognition method based on mobile phone signaling data includes the following steps:

[0041] Step 1. Select the base station near the target airport, take "day" as the unit, extract all the mobile phone signaling data captured by each base station within 0-24 hours of at least seven days, and make sure that the mobile device identification code in the signaling data is not repeated Save and generate an airport mobile phone user table.

[0042] The longer the extraction time and the more data extracted, the more comprehensive and reliable the information contained. This application sets the time extraction width as seven days, and in practical applications, the time width can be freely adjusted according to needs and accuracy. In order to minimize redundancy, the same mobile device identification code that occurs multiple times in the same day is stored as the same user.

[0043] The mobile phone ...

Embodiment 2

[0082] Different from Example 1, there are also preferred steps in this method.

[0083] In the airport mobile phone user table obtained in step 1, delete the mobile device identification codes that appear for 3 consecutive days or more from the airport mobile phone user table. Because, according to experience, if the mobile device identification code appears at the airport for 3 consecutive days, then the user of this device, that is, the mobile phone user, is basically a resident resident near the airport or an airport staff. Not included in the classification, so we delete such users from the airport mobile phone user table. It is calculated that Shijiazhuang Airport had a total of 49,962 air passengers during this period, of which 18,585 entered from outside the province, 974 entered from within the province, 26,350 departed from the province, and 26,350 departed from the province. There were 856 passengers, 2,661 transit passengers from outside the province to other prov...

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Abstract

The invention discloses an airport aviation passenger classification and identification method based on mobile phone signaling data. The method comprises the following steps: firstly, extracting mobile phone signaling data of base stations around a target airport; generating an airport user mobile phone table, tracing the current day signaling of the mobile phone user in the table; obtaining an integrated dataset, preprocessing the data set, dividing the data set into three types of data sets, classifying the mobile device identification codes in the airport mobile phone user table by referring to the three types of data sets and a preset aviation passenger identification rule, and finally counting the number of each type of mobile phone users to obtain target airport aviation passenger source distribution characteristics. According to the method, various aviation passengers, such as inbound passengers, outbound passengers, transit passengers and the like, in the airport can be automatically identified by utilizing mobile phone signaling data, passenger source distribution information of the various aviation passengers is counted, and a foundation is laid for subsequent research ontravel behavior characteristics of the various aviation passengers and depiction of an airport ventral space-time pattern.

Description

technical field [0001] The invention relates to the field of big data computing, in particular to a method for classifying and identifying air passengers at airports based on mobile phone signaling data. Background technique [0002] At present, the demand for air transportation is growing rapidly, and the throughput of global airports continues to increase. In 2018, the world's scheduled flights carried a total of 4.4 billion passengers, an increase of 6.9% over 2017, and 284 million new passengers. From 2013 to 2018, my country's civil aviation passengers increased from 354 million to 612 million, with an average annual growth rate of 11.56% over the past five years. The rapid growth of air passenger traffic has led to a rapid increase in airport ground traffic volume, which has brought great challenges to the ground traffic control around the airport. [0003] In order to continuously optimize the travel experience of air passengers, scholars at home and abroad pay grea...

Claims

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Application Information

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IPC IPC(8): G06F16/28G06F16/2455G06F16/215G06F16/2458H04W4/20H04W8/20
CPCG06F16/285G06F16/2477G06F16/215G06F16/24564H04W4/20H04W8/20
Inventor 刘劲松姚海芳
Owner HEBEI NORMAL UNIV
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