Mining method of user commuting od in mobile phone call data

Abstract

The invention discloses a method for mining user commuting OD in mobile phone call data. The number of calls of each mobile phone number in different base station locations; 3) Combine adjacent call base stations with overlapping coverage into one base station area, and count the number of calls of each mobile phone number in the base station area; 4) According to the number of calls of each mobile phone number in the base station area The number of calls determines the residence and work of the user of the mobile phone number, and the base station area with a high number of calls is the residence or work of the user. The method of the invention can obtain the commuting OD information of large-scale people, and has a wide coverage; because the data used is mobile phone call data, the cost is low; because the base station is used as the location unit, and the coverage of the base station is small, the obtained data information The granularity of the information obtained by the method of traditional commuter OD survey is finer.

Description

technical field [0001] The invention belongs to the field of computer technology and mobile communication technology, and relates to a method for mining user commuting OD by using mobile communication data. Background technique [0002] Commuting travel is the most basic and important travel for urban residents. It is a travel produced by the spatial separation of the place of residence and the place of work, and is an inevitable phenomenon in an industrialized society. Compared with other trips, commuting travel has greater invariance in time and space, and its timing affects other activities and trips of urban residents. So in a sense commuting is the basis for other activities. Especially with the expansion of the scope of employment of urban residents, commuting travel presents the characteristics of large-scale quantity, complex form, and centralized time and space. The traffic congestion in the city's morning and evening peaks caused by the concentration of time and ...

AI Technical Summary

Problems solved by technology

[0005] 2. The investigation process is cumbersome and expensive

Traffic surveys need to consume a lot of manpower, material and financial resources. Even for some urban populations, it often takes tens of thousands or even hundreds of thousands of funds to investigate the traffic travel data of tens of thousands of people.

Moreover, due to the periodicity of traffic surveys, large-scale traffic surveys need to be carried out periodically, so this type of survey data needs to be obtained repeatedly, and the cost of manpower and material resources is even more serious.

[0006] 3. Strong subjectivity, large data deviation, etc.

But its shortcomings are also very obvious, because the penetration rate of GPS devices in the market is not very high, so the user range is limited

And because the users who use GPS have their own characteristics, this method can only be limited to some groups of people, and the coverage area is small

In addition, the price of GPS devices is relatively high

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