CN111212383A - Method, device, server and medium for determining number of regional permanent population - Google Patents
Method, device, server and medium for determining number of regional permanent population Download PDFInfo
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- CN111212383A CN111212383A CN201811296748.5A CN201811296748A CN111212383A CN 111212383 A CN111212383 A CN 111212383A CN 201811296748 A CN201811296748 A CN 201811296748A CN 111212383 A CN111212383 A CN 111212383A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
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- H—ELECTRICITY
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- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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Abstract
The embodiment of the invention discloses a method, a device, a server and a medium for determining the number of regional permanent population. The method comprises the following steps: determining the number of resident devices in a target area according to the resident position of the mobile device, wherein the resident position of the mobile device is determined according to the positioning track data of the mobile device and the device behavior characteristics associated with the positioning track data; and determining the number of the permanent population of the target area according to the number of the resident devices of the target area. The technical scheme of the embodiment of the invention can master the number of the permanent population in any area in the city, thereby improving the area precision and the accuracy of the number of the permanent population.
Description
Technical Field
The embodiment of the invention relates to the technical field of data processing, in particular to a method, a device, a server and a medium for determining the number of population living in an area.
Background
The standing population is the core statistical indicator in city management. The statistics of the standing population can help governments to master the standing population number and the change trend of any region of a city, provide strong support for aspects such as city management, city planning, traffic management, city safe operation and the like, and also provide support for business location selection, marketing and other operation decisions of enterprises.
At present, the standing population is mainly determined by means of sampling survey or mobile phone signaling statistics and the like. The sampling survey is that a surveyor randomly extracts part of survey objects, performs personal information survey by adopting a survey questionnaire and other modes, and performs statistical analysis on data obtained by the survey. The mobile phone signaling statistics is to collect signaling data generated by a mobile communication terminal user in the process of using mobile equipment to communicate, acquire communication behavior information of the user, use the position of basic communication equipment (such as a base station) used when communication behavior is generated as the user position, and determine the population number of a target area according to the communication behavior information and the user position.
However, the sampling survey mode needs a large amount of manpower and material resources, the survey period is long, the sampling proportion is small, and the survey result is not accurate enough; the accuracy of the statistical position information of the mobile phone signaling is low, the number of the daily population in a small area (such as a street and a community) cannot be accurately counted, and the area accuracy is low.
Disclosure of Invention
The embodiment of the invention provides a method, a device, a server and a medium for determining the number of the permanent population in an area, which can master the number of the permanent population in any area in a city, and improve the area precision and the accuracy of the number of the permanent population.
In a first aspect, an embodiment of the present invention provides a method for determining a number of a regional permanent population, where the method includes:
determining the number of resident devices in a target area according to the resident position of the mobile device, wherein the resident position of the mobile device is determined according to the positioning track data of the mobile device and the device behavior characteristics associated with the positioning track data;
and determining the number of the permanent population of the target area according to the number of the resident devices of the target area.
In a second aspect, an embodiment of the present invention further provides an apparatus for determining the number of the area standing population, where the apparatus includes:
the device number determining module is used for determining the resident device number of the target area according to the resident position of the mobile device, wherein the resident position of the mobile device is determined according to the positioning track data of the mobile device and the device behavior characteristics related to the positioning track data;
and the population number determining module is used for determining the number of the permanent population of the target area according to the number of the resident equipment of the target area.
In a third aspect, an embodiment of the present invention further provides a server, including:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a method for determining a number of frequent population areas as described in any embodiment of the invention.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for determining the number of the area permanent population according to any embodiment of the present invention.
According to the scheme of the embodiment of the invention, the resident equipment number of the target area is determined according to the positioning data of the mobile equipment and the equipment behavior characteristics associated with the positioning data, so that the permanent population number of the target area is determined. The number of the permanent population in any area in the city can be mastered, the area precision is improved, and the accuracy of the number of the permanent population is improved.
Drawings
Fig. 1 is a flowchart of a method for determining a number of population living in a region according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for determining the number of the area permanent population according to a second embodiment of the present invention;
fig. 3 is a flowchart of a method for determining the number of the area permanent population according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an apparatus for determining the number of population living in a region according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of a server according to a fifth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a method for determining the number of the population living in an area according to an embodiment of the present invention, where the embodiment is applicable to a case where the number of the population living in an area is counted, and the method may be executed by a device or a server for determining the number of the population living in an area according to an embodiment of the present invention, and the device may be implemented in a hardware and/or software manner. As shown in fig. 1, the method specifically comprises the following steps:
s101, determining the resident equipment number of the target area according to the resident position of the mobile equipment, wherein the resident position of the mobile equipment is determined according to the positioning track data of the mobile equipment and the equipment behavior characteristics related to the positioning track data.
The resident location of the mobile device may refer to a location area where the frequency of the mobile device is high for m consecutive months, and optionally, m may be greater than 6 months in the judgment standard of the population living normally. Since a mobile device is typically held by a user, the resident location of the mobile device is the location where the user of the mobile device lives for m months. Optionally, the resident location of the mobile device may include: the mobile subscriber's residence, the mobile subscriber's units, or the frequent mall streets. Alternatively, the present invention is used to determine the number of surviving people, and thus, the mobile user may have m consecutive months of residence as the resident location of the mobile device. The target area may refer to an area to be subjected to demographics, which may be a country, province, city, county, etc., and may also be divided according to a certain rule, such as the Yangtze river delta area, the Zhujiang delta area, etc. The Positioning track data of the mobile device may be Positioning track data obtained by acquiring Positioning data (i.e., geographical position coordinate data of the mobile device) of the mobile device by a satellite Positioning module (e.g., a Global Positioning System (GPS)) configured on the mobile device and processing the Positioning data within a period of time. The device behavior feature associated with the positioning track data may be a behavior feature of the mobile device corresponding to the mobile device when the mobile device acquires each positioning data in the positioning track data, for example, the feature may include at least one of a time distribution of the mobile device corresponding to the acquisition of each positioning data, information of a point of interest near a current location, search behavior information on the mobile device, or a network type to which the mobile device is connected.
Optionally, in the embodiment of the present invention, to determine the number of devices resident in the target area, the location of each mobile device needs to be determined. Specifically, when the resident position of the mobile device is determined according to the positioning track data of the mobile device and the device behavior feature associated with the positioning track data, whether the device behavior feature associated with the positioning track data meets the preset requirement or not may be analyzed, and then the resident position of the mobile device is determined from the positioning track data. For example, according to the habit that people usually have a rest at home at night, the time distribution corresponding to the positioning track data of m months is analyzed, and the position area where the time distribution of the positioning track data is distributed at night and the occurrence frequency of the positioning track data is the highest is selected as the resident position of the mobile device; or according to the habit that people usually connect with a fixed type network in the home after returning home, analyzing the network type connected with the mobile equipment corresponding to the positioning track data of m months, and selecting a position area with the highest frequency of the same network type in the positioning track data as the resident position of the mobile equipment; the method can also be characterized in that according to the characteristic that the position of the interest point is fixed, nearby interest point information corresponding to the positioning track data of m months is analyzed, and a position area with the highest occurrence frequency of the same interest point information in the positioning track data is selected as a resident position of the mobile equipment; or analyzing the search behavior of the mobile device corresponding to the positioning track data of m months according to the habits of news, weather, maps and the like of the area where the user usually pays more attention to, and taking the position area with the highest occurrence frequency of the search target area corresponding to the search behavior as the resident position of the mobile device.
Optionally, in order to improve the accuracy of determining the resident location of the mobile device, at least two of the above determination methods may be combined to determine the resident location of the mobile device from the positioning track data. Specifically, similar to the above determination method, a determination condition may be set for each device behavior feature, the device behavior feature corresponding to the positioning track data of m months is analyzed, and a location area corresponding to a determination condition that continuously satisfies a certain device behavior feature or a determination condition that continuously satisfies all device behavior features is used as the resident location of the mobile device.
Alternatively, the resident location of each mobile device may be determined according to a pre-trained neural network-based resident location determination model, specifically, the positioning track data of the mobile device for m months and the device behavior characteristics associated with the positioning track data may be input into a trained resident location determination module, and the model outputs the resident location of the mobile device through analysis.
For example, when the number of the resident devices in the target area is determined based on the resident locations of the mobile devices, the number of the mobile devices corresponding to the resident location information in the target area may be searched from the resident location information of all the mobile devices counted by the server after the resident locations of the mobile devices are determined, and the number of the resident devices in the target area may be determined.
And S102, determining the number of the permanent population of the target area according to the number of the resident devices of the target area.
The population of the permanent population refers to the population living at home for more than 6 months all the year round, and also includes the floating population living in cities for more than 6 months.
For example, when the number of the target area permanent population is determined according to the number of the resident devices in the target area, the number of the resident devices continuously resident in the target area for more than 6 months in the target area may be used as the number of the target area permanent population.
Optionally, in order to improve the accuracy of determining the number of the permanent population of the target area, the number of the permanent population of the target area may be determined according to the number of the resident devices of the target area and the population fitting coefficient of the target area. The population fitting coefficient of the target area may be calculated and determined according to a certain operational relationship between the historical resident device number and the actual population number of the target area, and may be used to estimate parameter values of the resident device number and the actual population number of the current target area. Specifically, when the number of the resident devices in the target area and the population fitting coefficient of the target area are determined, the number of the resident devices in the target area may be obtained by multiplying the number of the resident devices in the target area by the population fitting coefficient of the target area, or may be determined by being introduced into other formulas, which is not limited in the present invention.
The embodiment provides a method for determining the number of the permanent population of an area, which determines the number of resident devices in a target area according to positioning data of a mobile device and device behavior characteristics associated with the positioning data, and further determines the number of the permanent population of the target area. The number of the permanent population in any area in the city can be mastered, the area precision is improved, and the accuracy of the number of the permanent population is improved.
Example two
Fig. 2 is a flowchart of a method for determining the number of the area permanent population according to the second embodiment of the present invention, which is further optimized based on the above embodiments, and specifically gives a detailed description of how to determine the resident location of the mobile device. As shown in fig. 2, the method includes:
s201, clustering positioning track data of the mobile equipment to obtain at least one track cluster.
Optionally, the clustering of the positioning track data is a process of dividing each set of positioning data in the positioning track data into track clusters having the same characteristics. Specifically, when clustering is performed on each positioning data in the positioning track data, the positioning data belonging to the same time period in the positioning track data may be clustered according to a time characteristic to obtain a track cluster in the time period, for example, the positioning data belonging to the same time period from eight am to ten am in the positioning track data may be clustered into a track cluster, and the positioning data belonging to the same time period from ten am to two pm in the positioning track data may be clustered into another track cluster; or clustering the positioning data in the same area in the positioning track data according to the area characteristics to obtain a track cluster of the area, for example, clustering the positioning data in the positioning track data and the positioning data in a street area belonging to a certain city into a track cluster. Other clustering manners can be selected in the embodiment of the present invention, which is not limited in this respect.
Optionally, the triggering condition for clustering the positioning track data of the mobile device may be that, every time a preset period (for example, one day) is reached, clustering the positioning data of the mobile device in the period is triggered, or the acquired positioning data is stored in the server, and when the storage memory of the server is smaller than a preset threshold, clustering the positioning data of the mobile device is triggered, and the like, which is not limited in the embodiment of the present invention.
S202, selecting a resident position cluster from at least one track cluster according to the equipment behavior characteristics of each track cluster.
The equipment behavior characteristics of the track cluster comprise at least one of time distribution of each track data in the track cluster, interest point information of the track cluster, network types and search behaviors. Specifically, the time distribution of each trace data may be a time distribution range when each trace point in the trace cluster is acquired, for example, the earliest time and the latest time corresponding to each trace data in the trace cluster may be respectively used as the starting time and the ending time of the time distribution; the interest point information of the track cluster can be the name, type, position and other information of the interest points around the track cluster; the network type may be a type of the mobile device connecting to the network when acquiring the trajectory data, and may include: optionally, in order to ensure consistency of network types, the network types may further specifically include Service Set Identifier (SSID) information of the network, and the like; the search behavior may be triggered search behavior information of the user on the mobile device when acquiring the positioning data, and may include, for example, content of the search, frequency of the search, time of viewing, and the like. Optionally, the device behavior feature of each track cluster may be extracted by the feature extraction module on the mobile device from data used by the mobile device or applications accessed from the mobile device, when the positioning module on the mobile device obtains the positioning data of the mobile device.
Optionally, when the resident location cluster is selected from the at least one track cluster according to the device behavior characteristics of each track cluster, a determination condition may be set according to each device behavior characteristic, and the resident location cluster may be selected from the at least one track cluster according to the determination condition corresponding to the set one or more device behavior characteristics. The resident position cluster determination model based on the neural network can be trained to judge whether each track cluster is a resident position cluster or not according to the equipment behavior characteristics of each track cluster. Specifically, the resident location cluster determination model may be a binary classification model, and each trajectory cluster and its corresponding device behavior characteristics may be input into a trained binary classification model, which may analyze and output a judgment whether the trajectory cluster is a resident location cluster; the resident location cluster determination model may also be a selection model, and all the trajectory clusters and their corresponding device behavior characteristics are input into a trained selection model, and the model selects a resident location cluster from a plurality of trajectory clusters through analysis.
Optionally, the resident location cluster determination model in the embodiment of the present invention may be a machine learning model, and may collect training samples in advance, train the initial neural network model based on the collected training samples, and finally obtain a resident location cluster determination model for selecting a resident location from at least one track cluster. For example, the elements included in each set of training samples may include: a plurality of track clusters corresponding to the mobile device, device behavior characteristics associated with each track cluster, and a resident location cluster of the mobile device. The algorithms employed may include Recurrent Neural Networks (RNNs), Long-Short Term Memory (LSTM) networks, threshold cycle units, simple cycle units, autoencoders, decision trees, random forests, feature mean classifications, classification regression trees, hidden markov, K-nearest neighbor (KNN) algorithms, logistic regression models, bayesian models, gaussian models, and KL divergences (Kullback-Leibler divergence), among others.
S203, determining the resident position of the mobile equipment according to the track data included in the resident position cluster.
Optionally, in the embodiment of the present invention, there are many methods for determining the resident location of the mobile device according to each piece of track data included in the resident location cluster, which are not limited herein. For example, the center of the area may be used as the resident location of the mobile device by fitting the area enclosed by the trajectory data in the resident location cluster; the distribution density of each trace data in the resident position cluster may be analyzed, and the center of the area with the high distribution density of the trace data may be used as the resident position.
S204, determining the resident equipment number of the target area according to the resident position of the mobile equipment.
And S205, determining the number of the permanent population of the target area according to the number of the resident devices of the target area.
The embodiment provides a method for determining the number of population living in an area, clustering at least one track cluster for a mobile device, selecting a resident location cluster from the track clusters according to the device behavior characteristics of each track cluster, and determining the resident location of the mobile device; when the number of the target area population is determined, the number of resident equipment in the target area is determined, and then the number of the permanent population in the target area is determined. The resident position of the mobile equipment is determined based on the track cluster and the equipment behavior characteristics of the track cluster, so that the accuracy of determining the resident position of the mobile equipment is improved, and the accuracy of determining the population quantity is further improved.
EXAMPLE III
Fig. 3 is a flowchart of a method for determining the number of the area permanent population according to a third embodiment of the present invention, which provides a preferred embodiment based on the above embodiments. As shown in fig. 3, the method includes:
s301, clustering positioning track data of the mobile equipment to obtain at least one track cluster.
Illustratively, a map software development platform (positioning SDK) and an equipment feature extraction module are deployed in each mobile equipment in advance, the positioning SDK acquires positioning data of the mobile equipment (the positioning SDK may acquire the positioning data in real time, or acquire the positioning data once every preset time interval, or start to acquire when the mobile equipment is detected to be in a motion state), the feature extraction module extracts behavior features of the mobile equipment when the positioning SDK acquires the positioning data, and uploads the positioning data and the behavior features of the mobile equipment associated with the positioning data to a server after a corresponding relationship is established between the positioning data and the behavior features of the mobile equipment. And after the server receives the positioning data sent by each mobile device and the device behavior characteristics corresponding to each positioning data, clustering the positioning data of each mobile device, and clustering at least one track cluster for each mobile device.
S302, selecting a resident position cluster from at least one track cluster according to the equipment behavior characteristics of each track cluster.
Optionally, the trajectory clusters and the device behavior characteristics of the trajectory clusters are input into a pre-trained resident location cluster determination model, and the model can select a resident location cluster from at least one trajectory cluster through analysis and calculation. Optionally, if there is no resident location cluster in at least one track cluster, the model outputs a prompt that there is no resident location cluster.
S303, determining the resident location of the mobile device according to each trace data included in the resident location cluster.
S304, determining the resident equipment number of the target area according to the resident position of the mobile equipment.
For example, when the number of the resident population in the target area is to be determined, the number of the mobile devices whose resident position coordinate information is within the target area coordinate range is counted as the number of the resident devices in the target area according to the resident position coordinate information of each mobile device determined in S303.
And S305, determining the number of the permanent population of the target area according to the number of the resident devices of the target area and the population fitting coefficient of the target area.
Optionally, the number of the permanent population of the target area is determined according to the number of the resident devices of the target area and the population fitting coefficient of the target area, and may be calculated according to the following formula:
s＝d×ait，
wherein s is the number of the permanent population of the target area, and d is the number of the resident equipment of the target area; a isitFitting coefficients for the population of the t year of the target city i.
For example, if the target city i belongs to the target area, when the number S of the population living in 2018 of the target area is to be determined, the number S of the resident devices in the target area determined in S304 may be multiplied by the population fitting coefficient in 2018 of the target city i.
Optionally, the population fitting coefficient of the target area may be determined by calculating according to a certain operational relationship between the historical resident device number and the actual population number of the target area, and specifically, the determining method of the population fitting coefficient of the target area includes the following steps:
A. and determining the historical resident equipment number of the target city to which the target area belongs.
The target area may be a country, province, city, county, etc., and may be divided according to a certain rule, such as the Yangtze river delta area, the Zhujiang river delta area, etc. Accordingly, the target city to which the target area belongs may be one or more.
Optionally, the historical resident device number of each city may be the resident device number of the previous year of the current year, or may be the average of the resident device numbers of the previous N (N is a positive integer greater than 1) years of the current year. The resident locations of the mobile devices are determined through S303 and then stored in the server, specifically, each city, the number of the resident devices corresponding to each city, and the year in which the resident locations are determined may be correspondingly stored in the server, and when the historical resident device number of the target city to which the target area belongs is determined, the target city may be directly searched from the server, and the historical resident device number of the target city may be obtained.
B. Acquiring the official historical frequent population number of the target city.
The official historical number of the permanent population of the city can be the number of the permanent population of each city published in the Chinese population information network in the past year. Alternatively, the number of the perennial population may be the number of the perennial population in the previous year of the year, or may be the average of the number of the perennial population in the previous N (N is a positive integer greater than 1) years of the year. The historical resident equipment quantity in the step a and the historical permanent population quantity in the step B have a certain corresponding relationship, if the historical resident equipment quantity is the previous year of the current year, the historical permanent population quantity is also the previous year of the current year, and if the historical resident equipment quantity is the previous N years of the current year, the historical permanent population quantity is also the previous N years of the current year.
Optionally, when acquiring the official historical population number of the permanent population of the target city, the server may search the target city and the year of the permanent population number to be acquired by accessing a website (such as a chinese population information network) for which the national official publishes population information, and further acquire the historical permanent population number of the target city; optionally, in order to prevent the problem that the acquisition of the historical population number of the permanent living is failed due to poor network, the server may store the historical population number of the permanent living in each city disclosed in the chinese population information network in the server when the network condition is good, and periodically detect whether the data in the chinese population information network is updated, and if so, update the data stored in the server. At the moment, the official historical frequent population number of the target city can be obtained by directly searching from the inside of the server, so that the searching efficiency is improved.
C. And determining population fitting coefficients of the target area according to the historical resident equipment number, the historical population number of the permanent dwellings and the natural growth rate of the historical permanent population of the target city.
The natural population growth rate is a ratio of a natural population increase (birth number minus death number) to an average population (or middle population) in a certain period (usually one year), and is generally expressed by a thousandth ratio, and a specific calculation formula may be: the natural growth rate of the population is (number of births within a year-number of deaths within a year)/average number of people per year multiplied by 1000 per mill.
Optionally, the population fitting coefficient of the target area is determined according to the historical resident device number, the historical population number of the permanent dwellings and the natural growth rate of the historical permanent population of the target city, and may be calculated according to the following formula:
wherein, aitFitting coefficients for the population of the t year of the target city i; c. Cit-1The number of resident equipment in the t-1 year of the target city i; git-1The official historical population number of the target city i in the t-1 year βiThe natural growth rate of the population is held for the history of the target city i.
For example, if the population fitting coefficient of the target city i in 2018 is to be determined, the population fitting coefficient of the target city i in 2018 may be determined based on the number of resident devices in the previous year (i.e., 2017) of the target city i, the number of official permanent population of the target city i in 2017, and the natural growth rate of the permanent population of the target city i from 2016 to 2017.
The embodiment provides a method for determining the number of the population of the permanent residence in the area, which determines the resident location of each mobile device through the track cluster and the device behavior characteristics of the track cluster, and when determining the number of the population of the target area, first determines the number of the resident devices in the target area and the calculated population fitting coefficient of the target area, and determines the number of the population of the permanent residence in the target area. Compared with the method that the resident equipment number of the target area is directly used as the number of the constant population of the target area, the number of the constant population obtained through calculation based on the population fitting coefficient of the target area is more accurate, and the area precision and the accuracy of the number of the constant population are improved.
Example four
Fig. 4 is a schematic structural diagram of a device for determining the number of the area permanent population according to a fourth embodiment of the present invention, which can execute the method for determining the number of the area permanent population according to any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method. As shown in fig. 4, the apparatus includes:
a device number determining module 401, configured to determine the number of resident devices in the target area according to a resident location of the mobile device, where the resident location of the mobile device is determined according to the location trace data of the mobile device and the device behavior characteristics associated with the location trace data;
a population number determining module 402, configured to determine the number of the permanent population of the target area according to the number of the resident devices of the target area.
The embodiment provides a device for determining the number of the population living in an area, which determines the number of resident devices in a target area according to positioning data of a mobile device and device behavior characteristics associated with the positioning data, and further determines the number of the population living in the target area. The number of the permanent population in any area in the city can be mastered, the area precision is improved, and the accuracy of the number of the permanent population is improved.
Further, the above apparatus further comprises:
the track clustering module is used for clustering positioning track data of the mobile equipment to obtain at least one track cluster;
a resident cluster selection module, configured to select a resident location cluster from the at least one track cluster according to the device behavior characteristics of each track cluster;
and the resident position determining module is used for determining the resident position of the mobile equipment according to the track data included in the resident position cluster.
The equipment behavior characteristics of the track cluster comprise at least one of time distribution of each track data in the track cluster, interest point information of the track cluster, network types and search behaviors.
Further, the population number determining module 402 is specifically configured to:
and determining the number of the permanent population of the target area according to the number of resident equipment of the target area and the population fitting coefficient of the target area.
Further, the population number determining module 402 is specifically configured to:
determining the historical resident equipment number of a target city to which the target area belongs;
acquiring the official historical permanent population number of the target city;
and determining population fitting coefficients of the target area according to the historical resident equipment number, the historical population number of the permanent dwellings and the natural growth rate of the historical permanent population of the target city.
EXAMPLE five
Fig. 5 is a schematic structural diagram of a server according to a fifth embodiment of the present invention. Fig. 5 illustrates a block diagram of an exemplary server 50 suitable for use in implementing embodiments of the present invention. The server 50 shown in fig. 5 is only an example, and should not bring any limitation to the function and the scope of use of the embodiment of the present invention. As shown in fig. 5, the server 50 is in the form of a general purpose computing device. The components of the server 50 may include, but are not limited to: one or more processors or processing units 501, a system memory 502, and a bus 503 that couples the various system components (including the system memory 502 and the processing unit 501).
The server 50 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by server 50 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 502 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)504 and/or cache memory 505. The server 50 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 506 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 503 by one or more data media interfaces. System memory 502 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 508 having a set (at least one) of program modules 507 may be stored, for example, in system memory 502, such program modules 507 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may include an implementation of a network environment. Program modules 507 generally perform the functions and/or methodologies of embodiments of the invention as described herein.
The server 50 may also communicate with one or more external servers 509 (e.g., keyboard, pointing device, display 510, etc.), with one or more devices that enable a user to interact with the device, and/or with any devices (e.g., network card, modem, etc.) that enable the server 50 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 511. Also, the server 50 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet) via a network adapter 512. As shown in FIG. 5, the network adapter 512 communicates with the other modules of the server 50 via the bus 503. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the server 50, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 501 executes various functional applications and data processing by executing programs stored in the system memory 502, for example, to implement the method for determining the number of the population living in the area provided by the embodiment of the present invention.
EXAMPLE six
The sixth embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, can implement the method for determining the number of the area permanent population according to the foregoing embodiment.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer-readable storage medium may be, for example but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The above example numbers are for description only and do not represent the merits of the examples.
It will be appreciated by those of ordinary skill in the art that the modules or operations of the embodiments of the invention described above may be implemented using a general purpose computing device, which may be centralized on a single computing device or distributed across a network of computing devices, and that they may alternatively be implemented using program code executable by a computing device, such that the program code is stored in a memory device and executed by a computing device, and separately fabricated into integrated circuit modules, or fabricated into a single integrated circuit module from a plurality of modules or operations thereof. Thus, the present invention is not limited to any specific combination of hardware and software.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts in the embodiments are referred to each other.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (12)
1. A method for determining a number of population living in a region, comprising:
determining the number of resident devices in a target area according to the resident position of the mobile device, wherein the resident position of the mobile device is determined according to the positioning track data of the mobile device and the device behavior characteristics associated with the positioning track data;
and determining the number of the permanent population of the target area according to the number of the resident devices of the target area.
2. The method of claim 1, wherein determining the number of resident devices of the target area based on the resident location of the mobile device comprises:
clustering positioning track data of the mobile equipment to obtain at least one track cluster;
selecting a resident position cluster from the at least one track cluster according to the equipment behavior characteristics of each track cluster;
and determining the resident position of the mobile equipment according to the track data included in the resident position cluster.
3. The method of claim 2, wherein the device behavior characteristics of the track cluster comprise at least one of a time distribution of each track data in the track cluster, interest point information of the track cluster, a network type, and a search behavior.
4. The method of claim 1, wherein determining the number of surviving population of the target area based on the number of resident devices of the target area comprises:
and determining the number of the permanent population of the target area according to the number of resident equipment of the target area and the population fitting coefficient of the target area.
5. The method of claim 4, wherein determining the population fit coefficients for the target region comprises:
determining the historical resident equipment number of a target city to which the target area belongs;
acquiring the official historical permanent population number of the target city;
and determining population fitting coefficients of the target area according to the historical resident equipment number, the historical population number of the permanent dwellings and the natural growth rate of the historical permanent population of the target city.
6. An apparatus for determining a population standing in a region, comprising:
the device number determining module is used for determining the resident device number of the target area according to the resident position of the mobile device, wherein the resident position of the mobile device is determined according to the positioning track data of the mobile device and the device behavior characteristics related to the positioning track data;
and the population number determining module is used for determining the number of the permanent population of the target area according to the number of the resident equipment of the target area.
7. The apparatus of claim 6, further comprising:
the track clustering module is used for clustering positioning track data of the mobile equipment to obtain at least one track cluster;
a resident cluster selection module, configured to select a resident location cluster from the at least one track cluster according to the device behavior characteristics of each track cluster;
and the resident position determining module is used for determining the resident position of the mobile equipment according to the track data included in the resident position cluster.
8. The apparatus of claim 7, wherein the device behavior characteristics of the track cluster comprise at least one of a time distribution of each track data in the track cluster, interest point information of the track cluster, a network type, and a search behavior.
9. The apparatus of claim 6, wherein the population number determination module is specifically configured to:
and determining the number of the permanent population of the target area according to the number of resident equipment of the target area and the population fitting coefficient of the target area.
10. The apparatus of claim 9, wherein the population number determination module is specifically configured to:
determining the historical resident equipment number of a target city to which the target area belongs;
acquiring the official historical permanent population number of the target city;
and determining population fitting coefficients of the target area according to the historical resident equipment number, the historical population number of the permanent dwellings and the natural growth rate of the historical permanent population of the target city.
11. A server, comprising:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a method of determining the number of population standing in a region as recited in any of claims 1-5.
12. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method of determining a number of regional persistent people as claimed in any one of claims 1 to 5.
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| CN112188478A (en) * | 2020-09-29 | 2021-01-05 | 浙江新再灵科技股份有限公司 | Resident population data acquisition method based on big data analysis |
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