Traffic mode discrimination method of semi-supervised SVM based on mobile phone signaling data

A technology of transportation mode and mobile phone signaling, applied in the field of computer identification, it can solve the problems of difficult identification accuracy of output categories, low data utilization rate, large workload, etc., and achieve the effect of improving classification efficiency.

Inactive Publication Date: 2019-05-21
SOUTHWEST JIAOTONG UNIV
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AI Technical Summary

Problems solved by technology

Cell phone signaling data is unlabeled data. If the method of supervised learning is used, a large amount of cell phone signaling data needs to be manually marked, which is a large workload and the data utilization rate is low; But the output class is difficult to identify and the accuracy is low

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  • Traffic mode discrimination method of semi-supervised SVM based on mobile phone signaling data
  • Traffic mode discrimination method of semi-supervised SVM based on mobile phone signaling data
  • Traffic mode discrimination method of semi-supervised SVM based on mobile phone signaling data

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Embodiment Construction

[0073] The specific technical solutions of the present invention are described in conjunction with the examples.

[0074] according to figure 1 The flow shown in this embodiment includes the following steps:

[0075] Step 1 Prepare and preprocess data

[0076] 1.1 Collect and prepare data

[0077] The invention adopts the mobile phone signaling data containing the travel chain information to study the discrimination method of the traffic mode. After the mobile phone signaling data is cleaned and mined, it is converted into the data set of the present invention. The data fields include user code, time stamp, track point latitude and longitude, track point type, user age, etc., user A0000001's date of Wednesday, September 14, 2016 The travel chain is shown in Table 1.

[0078] Table 1 User's full-day travel chain

[0079]

[0080] The origin-destination point indicates the starting point or end point of the trip, the stay point indicates that the user stays at the place,...

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Abstract

The invention relates to a computer identification technology, and specifically relates to a traffic mode discrimination method of semi-supervised SVM based on mobile phone signaling data. The methodcomprises: (1) preparing and preprocessing data; (2) designing label types; (3) extracting travel characteristics; (4) establishing an improved traffic mode manual identification process; (5) trainingan initial classifier; (6) judging the traffic mode of an unmarked sample; (7) judging whether the classifier meets a termination condition or not; (8) updating a high confidence coefficient sample data set; (9) optimizing a semi-supervised SVM classifier based on a Tri-training; (10) judging the traffic mode of an unmarked sample; (11) judging whether the classifier meets a termination condition; (12) updating a data set of a low-confidence sample; and (13) optimizing the shell vector-based semi-supervised SVM classifier. The information acquisition cost is reduced, the data utilization rateis improved, judgment is flexible and comprehensive, the precision is high, and the application scene is wider.

Description

technical field [0001] The invention relates to computer identification technology, in particular to a traffic mode discrimination method based on semi-supervised SVM of mobile phone signaling data. Background technique [0002] Travel mode information plays an important role and value in traffic planning, traffic control management and other aspects. At present, the methods of obtaining traffic information include two categories: traditional survey and data mining. Traditional survey methods such as questionnaire surveys and telephone inquiries are difficult to implement at high frequency and on a large scale, and cannot accurately reflect the actual transportation mode information; data mining methods are mainly based on mobile phone data to establish certain rules to mine transportation mode information. , the method of data mining can not only solve the shortcomings of difficult survey organization, low sampling rate, and single dimension of information display, but als...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G08G1/01
Inventor 张锦唐劲松冯雨庭肖斌罗静
Owner SOUTHWEST JIAOTONG UNIV
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