CN110930285B - Population distribution analysis method and device - Google Patents
Population distribution analysis method and device Download PDFInfo
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- CN110930285B CN110930285B CN202010080203.1A CN202010080203A CN110930285B CN 110930285 B CN110930285 B CN 110930285B CN 202010080203 A CN202010080203 A CN 202010080203A CN 110930285 B CN110930285 B CN 110930285B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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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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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/20—Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel
Abstract
The embodiment of the invention provides a population distribution analysis method and a device, wherein the method comprises the following steps: acquiring power consumption data of each land in a target area; identifying the type of the land parcel according to the electricity consumption data; acquiring signaling data of user equipment in a target area; determining a working place and a residence place in the target area according to the signaling data; determining the number of the users in the residential area according to the electricity consumption data; determining OD data according to the signaling data; determining a sample expansion coefficient according to the number of the users and the signaling data; and determining population distribution characteristics of the target area according to the sample expansion coefficient and the OD data. In the embodiment of the invention, the sample expansion coefficient is analyzed and calculated through the corresponding relation between the number of the electric users in the residential area and the signaling data of the user equipment, and the population distribution characteristics of the workplace and the rest area are obtained through the distribution of OD data.
Description
Technical Field
The embodiment of the invention relates to the technical field of traffic, in particular to a population distribution analysis method and device.
Background
The population factors determine the requirements of city development on natural resources, land, infrastructure and public service facilities to a great extent, and further have important influence on the spatial layout and the development direction of the city. As two major carriers of urban resident production and living, inhabitation and employment are two core endogenous variables in an urban space structure, and are dependently influenced mutually. Research and identification technologies triggered by the mastery of demographic activity distribution characteristics are receiving wide attention from the intelligent transportation industry.
The traditional mode of obtaining urban resident spatial distribution is mainly visiting, questionnaire survey etc. by visiting, this type of mode not only can consume a large amount of manpower and materials, and the sample quantity of acquireing moreover is also limited. In recent years, location-aware data based is becoming an emerging means of urban demographics.
Based on a Geographic Information System (GIS) and remote sensing data, urban potential population distribution characteristics are analyzed by measuring and calculating urban living areas and combining social and economic statistical data, but the method is a static statistical method, has limited accuracy and can not give dynamic distribution description of urban population.
Disclosure of Invention
The embodiment of the invention provides a population distribution analysis method and a population distribution analysis device, which solve the problems that the existing population analysis method is limited in accuracy and cannot provide dynamic distribution description of urban population.
In a first aspect, an embodiment of the present invention provides a population distribution analysis method, where the method includes:
dividing a target area into a plurality of plots, and acquiring power consumption data of each plot;
identifying the type of the land parcel according to the electricity consumption data;
acquiring signaling data of user equipment in a target area;
determining a place of work and a place of residence in the target area according to the signaling data;
determining the number of the electric consumers of the residential area according to the electricity consumption data;
determining traffic travel capacity (OD) data according to the signaling data;
determining a sample expansion coefficient according to the user number and the signaling data;
and determining population distribution characteristics of the target area according to the sample expansion coefficient and the OD data.
Optionally, the identifying the category of the parcel according to the power consumption data includes:
calculating the electricity utilization proportion of the land during the working time period through a first formula, and calculating the electricity utilization proportion of the land during the rest time period through a second formula;
the first formula is:
the second formula is:
in that
＜
And is
＜
In the case of (3), determining the category of the land parcel as a characteristic land parcel of a residential area;
in that
＞
And is
Determining the type of the land parcel as a mixed region characteristic land parcel;
in that
And is
＜
Determining the type of the land parcel as a characteristic land parcel of a working land;
wherein the content of the first and second substances,
representing the power usage of the plot during the work period
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing the electricity consumption of the plot during a rest period
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing the power usage of the plot during the work period
Account for the total daily electricity consumption
The proportional average number of (1);
representing the electricity consumption of the plot during a rest period
Account for the total daily electricity consumption
The ratio of (a) to (b).
Optionally, the determining a place of work and a place of residence in the target area according to the signaling data includes:
projecting all the stay points on a Geographic Information System (GIS) map according to the signaling data;
the residence is determined in all the residence points corresponding to the residence analysis period, and the work place is determined in all the residence points corresponding to the work place analysis period.
Optionally, determining the residence or the work place in all the dwell points comprises:
determining the staying points with the staying time not less than a first staying time threshold value in all the staying points as alternative staying points;
determining a dwell point, of all the alternative dwell points, of which the proportion of the dwell time in the preset time interval is not less than a preset dwell probability threshold value, as a first effective dwell point;
and determining the residence point with the longest residence time in all the first effective residence points as the residence place or the working place.
Optionally, the determining the traffic travel data OD according to the signaling data includes:
clustering a plurality of base stations in the target area;
determining a staying track of the user equipment according to the signaling data recorded by the base station after the clustering;
determining a dwell point in the dwell track, the dwell time of which is not less than a second dwell time threshold value, as a second effective dwell point;
traversing all the second effective stop points, and determining a travel starting and ending point of the user equipment;
and counting the OD data of the traffic travel amount between the start and the end of the travel.
Optionally, the determining a sample spreading factor according to the number of users and the signaling data includes:
establishing a corresponding relation between the user number and the signaling data;
fitting a curve according to the corresponding relation;
and determining the sample expansion coefficient according to the fitted curve.
In a second aspect, an embodiment of the present invention provides a population distribution analysis apparatus, including:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for dividing a target area into a plurality of plots and acquiring power consumption data of each plot;
the identification module is used for identifying the type of the land parcel according to the electricity consumption data;
a second obtaining module, configured to obtain signaling data of the user equipment in the target area;
a first determining module, configured to determine a work place and a residence place in the target area according to the signaling data;
the second determining module is used for determining the number of the electricity consumers of the residential area according to the electricity consumption data;
the third determining module is used for determining the OD data of the traffic volume according to the signaling data;
a fourth determining module, configured to determine a sample expansion coefficient according to the user number and the signaling data;
and the fifth determining module is used for determining the population distribution characteristics of the target area according to the sample expansion coefficient and the OD data.
Optionally, the identification module comprises:
the calculation unit is used for calculating the electricity utilization ratio of the land during the working period through a first formula and calculating the electricity utilization ratio of the land during the rest period through a second formula;
the first formula is:
the second formula is:
in that
＜
And is
＜
In the case of (3), determining the category of the land parcel as a characteristic land parcel of a residential area;
in
And is
Determining the type of the land parcel as a mixed region characteristic land parcel;
in that
And is
＜
Determining the type of the land parcel as a characteristic land parcel of a working land;
wherein the content of the first and second substances,
representing the power usage of the plot during the work period
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing the electricity consumption of the plot during a rest period
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing the power usage of the plot during the work period
Account for the total daily electricity consumption
The proportional average number of (1);
representing the electricity consumption of the plot during a rest period
Account for the total daily electricity consumption
The ratio of (a) to (b).
Optionally, the first determining module includes:
the projection unit is used for projecting all the stay points on a Geographic Information System (GIS) map according to the signaling data;
a first determination unit for determining the residence in all the residence points corresponding to the residence analysis time period and determining the work place in all the residence points corresponding to the work place analysis time period.
Optionally, the first determining unit includes:
the first determining subunit is used for determining a dwell point, of which the dwell time is not less than a first dwell time threshold value, in all the dwell points as a candidate dwell point;
the second determining subunit is used for determining a stopping point, of all the alternative stopping points, of which the ratio of the stopping time to the preset time interval is not less than the preset stopping probability threshold value as a first effective stopping point;
and the third determining subunit is used for determining the dwell point with the longest dwell time in all the first effective dwell points as the residence place or the working place.
Optionally, the third determining module includes:
the processing unit is used for clustering a plurality of base stations in the target area;
a second determining unit, configured to determine a staying track of the user equipment according to the signaling data recorded by the clustered base station;
a third determining unit, configured to determine a dwell point in the dwell trajectory, where the dwell time is not less than a second dwell time threshold, as a second effective dwell point;
a fourth determining unit, configured to traverse all the second valid stop points, and determine a trip start and end point of the user equipment;
and the statistical unit is used for counting the OD data between the beginning and the end of the trip.
Optionally, the fourth determining module includes:
the establishing unit is used for establishing the corresponding relation between the user number and the signaling data;
the fitting unit is used for fitting a curve according to the corresponding relation;
and the fifth determining unit is used for determining the sample expansion coefficient according to the fitted curve.
In the embodiment of the invention, the sample expansion coefficient is analyzed and calculated through the corresponding relation between the number of the electric users in the residential area and the signaling data of the user equipment, and the population distribution characteristics of the workplace and the rest area are obtained through the distribution of OD data.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts;
FIG. 1 is a schematic flow chart of a population distribution analysis method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of power consumption data provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram of a fitting curve provided by an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a population distribution analysis apparatus according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the embodiments of the present invention, words such as "exemplary" or "for example" are used to mean serving as examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "e.g.," an embodiment of the present invention is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.
Herein, relational terms such as "first" and "second", and the like, are used solely to distinguish one from another of like names, and do not imply a relationship or order between the names.
In order to facilitate understanding of the technical solutions of the present application, the following technical contents are first described:
(1) a population distribution analysis algorithm based on the mobile phone signaling data;
and 4, residential and travel characteristic analysis based on the mobile phone signaling data. The mobile phone signaling data has large sample amount, objective and comprehensive data and stronger space-time continuity, and the whole process of traffic travel can be observed. The population distribution analysis algorithm based on the mobile phone signaling data can make up for the characteristics of long periodicity, large workload and high cost of the traditional population survey. The system can realize urban population job and live analysis, trip characteristic analysis, trip analysis spatial distribution characteristic analysis, commuting trip analysis and all-day population activity distribution based on mobile phone signaling data.
And determining the position of a base station in the city by utilizing the Thiessen polygon, and taking the position of the base station where the user is located when the signaling data is generated as the geographic position of the user. After the employment place and the residence place of the user are obtained through the signaling data, the position of the base station corresponding to the employment place and the residence place is projected on a map to obtain the position distribution of residents, and the position distribution and the commuting distance of the residents in the central urban area and the peripheral areas are researched according to the position distribution and the commuting distance.
And acquiring the living information and employment information of residents by using the mobile phone signaling data of the residents, and generating the employment density distribution map by using the employment information. And identifying employment dense areas in the city by taking the employment density of the city center as a reference, and measuring the energy level of each dense area from the aspects of the employment density and the commute distance. And analyzing the core area and the radiation range of each employment center, and drawing conclusions about the radiation range, the commuting connection, the difference in position and the like of each employment center.
By processing the mobile phone signaling data, employment distribution data of residents are obtained, and the employment area migration trend of the residents is analyzed from the aspects of city population, city division and city streets, and the result shows that the employment area migration of the Shanghai city is mainly short-distance movement and migrates from the central area and the suburban area to the suburban area.
(2) An industry application technology based on electricity utilization big data;
the power consumption big data has the advantages of large data quantity, numerous data types, large data increment, high speed and the like. The daily increment is dozens of GB according to the upper general user electric quantity information data acquired by a single province power system every day and the intermediate data and the result data generated by later-stage calculation analysis. In recent years, the electricity consumption data is gradually applied to the aspects of urban development, such as the identification of urban active business circles and the industrial development law, but no related application technology exists in the aspect of population activity distribution.
Based on the above description, the mobile phone signaling data is widely applied to urban population distribution and traffic travel characteristic research. Because domestic mobile phone signaling data is mastered by several operators in mobility, communication and telecommunication, the data sources are dispersed, the signaling data is incompletely sampled, and each operator has certain difference in regional distribution, the accuracy of population distribution and travel characteristic data obtained by single mobile phone signaling data is lower.
The electricity utilization data has the characteristic of complete sampling and is gradually applied to the field of urban development research, but the electricity utilization data is spatially static data and has poor identification performance, and cannot be applied to activity tracks of micro population in research, so that the single electricity utilization data cannot be applied to researching the position relationship of the population.
Therefore, a high-precision population distribution analysis method based on the fusion of mobile phone signaling and power consumption is needed.
Referring to fig. 1, an embodiment of the present invention provides a population distribution analysis method, which includes the following specific steps:
step 101: dividing a target area into a plurality of plots, acquiring power consumption data of each plot, and executing step 102;
in the embodiment of the present invention, the target area refers to a research area when population distribution analysis is performed, and before analysis, the target area is divided into a plurality of plots, and power consumption data corresponding to each plot is obtained.
Step 102: identifying the type of the land parcel according to the electricity consumption data, and then executing a step 105;
in the embodiment of the invention, the type of the plot is identified based on the electricity consumption of the plot, and the type of the plot is used for representing the corresponding plot function of the plot.
Urban land use refers to conditions of construction land in cities, such as industry, traffic, commerce, culture, education, sanitation, housing, park greenbelts, and the like, and is a comprehensive result expressed by interaction between human social activities and urban material spaces, compared to urban land coverage. There is comparatively obvious functional partitioning in the urban land, classifies according to the industrial structure, mainly can divide into: commercial, industrial and residential areas.
Residential land: the residential area is a living space of urban residents, is widely distributed and is the type of land with the largest area in the city.
Industrial application site: the heavy industrial area occupies a large area, pollutes the environment, is not necessarily connected with the life of residents, and is generally distributed in suburban areas, the light industrial area mainly consumes and produces, is closely connected with the life of residents, and is generally distributed at the periphery of urban commercial areas or according to the population gathering degree.
Commercially available: the commercial area has small occupied area, is generally positioned in cities or regions, is also a hub of a whole-city traffic and communication network system, plays an important role in city economy and normal operation, and is particularly the region with the most concentrated and busy city economy activity.
The difference in urban activities between residential, industrial and commercial sites is in the overall activity versus time profile. The working time period is busy in the daytime and the rest time period is relatively free at night in the commercial place; the living land is idle in the working time period in the daytime, and is busy when the living rest function is carried at night.
Considering that the electricity consumption in different time periods is different in the distribution of the whole day time of the electricity consumption, in order to ensure that the measurement results in different time periods in one day are comparable, the initial data needs to be further processed to obtain the ratio of the time period to the average hour in the whole day.
The embodiment of the invention provides a method for identifying the type of a land parcel according to power consumption data, which comprises the following specific processes:
calculating the electricity utilization ratio of the plot in the working time period through a first formula, and calculating the electricity utilization ratio of the plot in the rest time period through a second formula;
the first formula is:
the second formula is:
in that
＜
And is
＜
Determining the type of the land parcel as a characteristic land parcel of the residential area;
in that
＞
And is
In the case of (2), determiningThe land parcel type is a mixed region characteristic land parcel;
in that
And is
＜
Determining the type of the land parcel as a characteristic land parcel of the working land;
wherein the content of the first and second substances,
indicating the electricity usage of a parcel during its working hours
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing electricity consumption of a parcel during a rest period
Account for the total daily electricity consumption
The ratio of (A) to (B);
indicating the electricity usage of a parcel during its working hours
Account for the total daily electricity consumption
The proportional average number of (1);
representing electricity consumption of a parcel during a rest period
Account for the total daily electricity consumption
The ratio of (a) to (b).
It can be understood that the working time period and the rest time period can be flexibly set according to the crowd corresponding to local activities in the land, and the specific time of the working time period and the rest time period is not limited in the embodiment of the invention.
Step 103: acquiring signaling data of user equipment in a target area, and then executing step 104 and step 106;
in the embodiment of the present invention, the user equipment refers to user equipment capable of being acquiring signaling data in a target area, and the user equipment may be equipment that a user can carry with, for example: mobile phones, tablet computers, notebook computers, and the like; the user equipment may also be a non-mobile fixed device, such as: a monitor, a server, etc., and the type of the user equipment is not particularly limited in the embodiment of the present invention.
Specifically, after the signaling data of the user equipment is acquired, the signaling data is firstly subjected to data cleaning to remove interference information and noise in the data.
The distribution characteristics of the user equipment on time and position can be obtained through the signaling data of the user equipment, and the distribution characteristics of the user can be represented by the distribution characteristics of the user equipment, so that the distribution characteristics of population in the target area can be obtained.
Specifically, population type distribution is performed according to signaling data of the user equipment, and population is generally divided into two major types by residence date, time and location of the population: a constant population (e.g., residence time of more than 7 hours/day, day of 50% or more, the 50% day being the percentage of residence time of 50% of the preset study days) and a non-constant population. The standing population is divided into resident people and fixed equipment, wherein the fixed equipment is identified as the fixed equipment with the positioning position unchanged all the time; on all the days of occurrence in the population, those with residence times less than 3 hours were identified as border crossing people, and others as floating people.
It should be understood that the above numerical values are only examples, and the embodiments of the present invention do not specifically limit the numerical values of the parameters.
Step 104: determining a place of work and a place of residence in the target area according to the signaling data, and then executing step 105;
in the embodiment of the invention, the workplace and the residence are identified in the target area based on the signaling data, so that the analysis of the position and residence characteristics of the population distribution is facilitated.
The embodiment of the invention provides a mode for determining a working place and a residence place in a target area, which comprises the following specific processes:
(1) projecting all the dwell points on a GIS map according to the signaling data;
in the embodiment of the present invention, travel is defined as the one-way travel distance of the resident exceeding a certain distance, for example: 500 m over a certain time, for example: 5 minutes of locomotor activity. With a GIS tool, all the dwell points can be projected on the map.
(2) Determining the residence in all the residence points corresponding to the residence analysis time period and determining the working place in all the residence points corresponding to the working place analysis time period;
and judging whether one stop point is a working stop point or a living stop point, wherein the time distribution characteristic, the communication type distribution characteristic, the communication frequency distribution characteristic and the like of the stop point can be utilized. In the embodiment of the invention, the type of the stop point is judged by using the time distribution characteristics of the working stop point and the dwelling stop point.
First, a residence analysis period and a workplace analysis period are divided, for example:
determining the residence analysis time period as: 19: 00-08: 00 the next day;
determining a working analysis time period as: 09:00-21:00 (this day);
then, the stay point with the stay time not less than the first stay time threshold value in all the stay points is determined as the alternative stay point. The dwell time refers to the cumulative dwell time of the user equipment at the base station, for example: the first dwell time threshold is set at 4 hours.
And then, determining the stay point, of all the alternative stay points, of which the proportion of the stay time to the preset time interval is not less than a preset stay probability threshold value as a first effective stay point. The effective stay place where each user appears in the working time (residence time) range and the stay days exceed the stay probability threshold value, which can be set according to other city experiences, for example: set to 0.5.
Finally, the residence point with the longest residence time of all the first effective residence points is determined as the residence or the working place, wherein the residence is determined during the residence analysis period and the working place is determined during the working analysis period.
It should be noted that the flow from step 101 to step 102 and the flow from step 103 to step 104 may be executed synchronously or sequentially, which is not specifically limited in this embodiment of the present invention.
Step 105: determining the number of the electricity consumers in the residential area according to the electricity consumption data, and then executing step 107;
in the embodiment of the invention, the number of the electric users is determined according to the residential area determined by the signaling data and the electricity consumption data of the residential area, the electric imbalance caused by the employment of families with electricity consumption peaks and valleys in working hours and rest hours is considered, and the number of the electric users is identified from the inside of the land, so that the number of the electric users is obtained.
Step 106: determining OD data according to the signaling data, and then executing step 107;
in the embodiment of the present invention, based on signaling data of a user device in a target area, traffic-departure (OD) data of a user is determined.
The embodiment of the invention provides a mode for determining OD data, which comprises the following specific processes:
(1) clustering a plurality of base stations in a target area;
in the embodiment of the invention, the base stations in a certain distance (which can be set according to the average service radius of the base stations) in the target area are clustered and combined according to the latitude and longitude information of the base stations.
(2) Determining a staying track of the user equipment according to the signaling data recorded by the base station after the clustering;
in the embodiment of the invention, the staying track of the user equipment is determined according to the base station after the aggregation treatment; although the user equipment sometimes does not shift, the recording position of the user equipment will jump between adjacent base stations, which is called ping-pong effect, in order to eliminate the ping-pong effect, the influence on the travel OD estimation is avoided, and at the same time, the short-distance travel which divides the long-distance travel into a plurality of times is avoided, and the base stations which are two or more times continuously in the user record are defined as the staying base stations.
(3) Determining a dwell point with the dwell time not less than a second dwell time threshold value in the dwell track as a second effective dwell point;
in the embodiment of the invention, an effective stay point in the effective stay track of each mobile phone user, the stay time of which is not less than the set stay time threshold value, is selected, and optionally, the stay time threshold value is set to be 1 hour, which corresponds to one purposeful trip.
(4) Traversing all the second effective stop points, and determining the trip starting and ending point of the user equipment;
in the embodiment of the invention, all the user effective stay tables are traversed, and the starting point and the ending point of the trip chain are judged.
(5) Counting OD data between the beginning and the end of a trip;
further, the judgment criterion for defining the residential area is that the base station with the longest residence time is 19: 00-08: 00 the next day is the residential base station based on the OD information and the work and rest time. 09:00-21:00 (the day) of the base station with the longest residence time, and the base station with residence time of more than 4 hours and days of more than or equal to 50 percent of days in the range of 500 meters around the base station is the working base station.
Step 107: determining a sample expansion coefficient according to the number of the users and the signaling data, and then executing step 108;
in the embodiment of the invention, as the signaling data is incompletely sampled, the data is subjected to data expansion by combining with the power consumption data, so that relatively complete population distribution information can be obtained. And calculating the sample expansion coefficient of the signaling data according to the corresponding relation between the signaling data of the residential block and the number of the users.
Specifically, a corresponding relation between the number of the users and the signaling data is established; fitting a curve according to the corresponding relation; and determining the sample expansion coefficient according to the fitted curve.
In some implementation scenarios, the sample expansion coefficient calculation process based on the signaling data and the power consumption data is as follows:
(1) the method comprises the steps of traversing the electricity utilization conditions of users with less electricity consumption by considering the actual conditions of the users, judging that the accumulated electricity consumption in 6 months is lower than 24kW & h, judging that the users are vacant, and removing the number of the electricity utilization users irrelevant to population distribution through the identification of vacant houses;
(2) and processing the electricity utilization data. The number of regional power utilization users cannot be judged simply by judging whether power utilization is available or not under the condition that no person in a family stays, and the number of the power utilization household in the same type is identified from a plot, wherein the number of the regional power utilization users is considered to be unbalanced in power utilization of the family with obvious power utilization difference between working hours and rest times; and marking the household users who use electricity without difference between the working time and the rest time as stay users.
(3) Referring to fig. 2, the abscissa of the graph is time, corresponding to the time from 0 hour to 24 hours of the whole day, in hours, and the ordinate is power consumption, in kilowatt-hours. And selecting a period with the electricity consumption larger than the daily average electricity consumption from the daily electricity consumption data as the electricity consumption peak period. Performing cluster analysis on the electricity utilization data, and counting the number of family households in each electricity utilization peak time period and recording as Fr;
(4) and dividing residential base stations of the signaling data based on the track data of the signaling data, and taking the base station with the longest residence time of 08:00 on the 19: 00-next day as the residential base station of the user. There are two types of situations for this type of user: 1. if the user is in the residential base station for a long time and is not going out, namely the user is still in the residential base station in working time, the number of the users is marked as Wt; 2. there is travel during the work period, and the population of such users is labeled Wr.
(5) The electricity consumption number (Wp) in the peak time period is not less than the peak electricity consumption number (Wt) multiplied by the average number of users;
(6) referring to fig. 3, in the graph, the abscissa corresponds to the population Wr of the trip in the working time period, the unit is a person, the ordinate corresponds to the peak-period electricity consumption population Wp, and the unit is a person, and a curve is fitted through the corresponding relationship between each peak-period electricity consumption population Wp and the population Wr of the trip in the working time period, so as to obtain the sample expansion coefficient ai of the block signaling data.
R2The fitting degree of the trend line is an index of the fitting degree of the trend line, the numerical value of the index can reflect the fitting degree between the estimated value of the trend line and corresponding actual data, and the higher the fitting degree is, the higher the reliability of the trend line is.
R2Is a value in the range of 0-1, as R of the trend line2When the reliability is equal to 1 or close to 1, the reliability is highest, otherwise, the reliability is lower. R2Also called decision coefficient.
Step 108: determining population distribution characteristics of a target area according to the sample expansion coefficient and the OD data;
in the embodiment of the invention, the travel distribution result of the OD data, the signaling data and the sample expansion coefficient are combined to obtain the population distribution of the workplace, the commuter population and the population travel characteristics of all time periods all day. Specifically, the population distribution characteristic analysis can be performed according to the sample expansion coefficient and the OD data by using the existing analysis algorithm, and the embodiment of the present invention does not limit the specific algorithm for determining the population distribution characteristic based on the sample expansion coefficient and the OD data.
In the embodiment of the invention, the sample expansion coefficient is analyzed and calculated through the corresponding relation between the number of the electric users in the residential area and the signaling data of the user equipment, and the population distribution characteristics of the workplace and the rest area are obtained through the distribution of OD data.
Referring to fig. 4, an embodiment of the present invention provides a population distribution analyzing apparatus 400, including:
a first obtaining module 401, configured to divide a target area into multiple plots, and obtain power consumption data of each plot;
an identification module 402, configured to identify a category of the parcel according to the power consumption data;
a second obtaining module 403, configured to obtain signaling data of a user equipment in a target area;
a first determining module 404, configured to determine a work place and a residence place in the target area according to the signaling data;
a second determining module 405, configured to determine, according to the power consumption data, the number of the electricity consumers in the residential area;
a third determining module 406, configured to determine traffic travel OD data according to the signaling data;
a fourth determining module 407, configured to determine a sample expansion coefficient according to the number of users and the signaling data;
a fifth determining module 408, configured to determine a population distribution characteristic of the target area according to the sample expansion coefficient and the OD data.
Optionally, the identifying module 402 includes:
the calculation unit is used for calculating the electricity utilization ratio of the land during the working period through a first formula and calculating the electricity utilization ratio of the land during the rest period through a second formula;
the first formula is:
the second formula is:
in that
＜
And is
＜
In the case of (3), determining the category of the land parcel as a characteristic land parcel of a residential area;
in that
＞
And is
Determining the type of the land parcel as a mixed region characteristic land parcel;
in that
And is
＜
Determining the type of the land parcel as a characteristic land parcel of a working land;
wherein the content of the first and second substances,
representing the power usage of the plot during the work period
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing the electricity consumption of the plot during a rest period
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing the power usage of the plot during the work period
Account for the total daily electricity consumption
The proportional average number of (1);
indicating that the electricity consumption of the land block accounts for the electricity consumption of the whole day in the rest time period
The ratio of (a) to (b).
Optionally, the first determining module 404 includes:
the projection unit is used for projecting all the stay points on a Geographic Information System (GIS) map according to the signaling data;
a first determination unit for determining the residence in all the residence points corresponding to the residence analysis time period and determining the work place in all the residence points corresponding to the work place analysis time period.
Optionally, the first determining unit includes:
the first determining subunit is used for determining a dwell point, of which the dwell time is not less than a first dwell time threshold value, in all the dwell points as a candidate dwell point;
the second determining subunit is used for determining a stopping point, of all the alternative stopping points, of which the ratio of the stopping time to the preset time interval is not less than the preset stopping probability threshold value as a first effective stopping point;
and the third determining subunit is used for determining the dwell point with the longest dwell time in all the first effective dwell points as the residence place or the working place.
Optionally, the third determining module 406 includes:
the processing unit is used for clustering a plurality of base stations in the target area;
a second determining unit, configured to determine a staying track of the user equipment according to the signaling data recorded by the clustered base station;
a third determining unit, configured to determine a dwell point in the dwell trajectory, where the dwell time is not less than a second dwell time threshold, as a second effective dwell point;
a fourth determining unit, configured to traverse all the second valid stop points, and determine a trip start and end point of the user equipment;
and the statistical unit is used for counting the OD data between the beginning and the end of the trip.
Optionally, the fourth determining module 407 includes:
the establishing unit is used for establishing the corresponding relation between the user number and the signaling data;
the fitting unit is used for fitting a curve according to the corresponding relation;
and the fifth determining unit is used for determining the sample expansion coefficient according to the fitted curve.
In the embodiment of the invention, the sample expansion coefficient is analyzed and calculated through the corresponding relation between the number of the electric users in the residential area and the signaling data of the user equipment, and the population distribution characteristics of the workplace and the rest area are obtained through the distribution of OD data.
The above description is only an embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present disclosure should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (12)
1. A method for analyzing a population distribution, the method comprising:
dividing a target area into a plurality of plots, and acquiring power consumption data of each plot;
identifying the type of the land parcel according to the electricity consumption data;
acquiring signaling data of user equipment in a target area;
determining a place of work and a place of residence in the target area according to the signaling data;
determining the number of the electric consumers of the residential area according to the electricity consumption data;
determining traffic travel volume (OD) data according to the signaling data;
determining a sample expansion coefficient according to the user number and the signaling data;
and determining population distribution characteristics of the target area according to the sample expansion coefficient and the traffic load (OD) data.
2. The method of claim 1, wherein identifying the category of the parcel based on the power usage data comprises:
calculating the electricity utilization proportion of the land during the working time period through a first formula, and calculating the electricity utilization proportion of the land during the rest time period through a second formula;
the first formula is:
the second formula is:
in that
＜
And is
＜
In the case of (3), determining the category of the land parcel as a characteristic land parcel of a residential area;
in that
＞
And is
Determining the type of the land parcel as a mixed region characteristic land parcel;
in that
And is
＜
Determining the type of the land parcel as a characteristic land parcel of a working land;
wherein the content of the first and second substances,
indicating that the plot is in operationElectricity consumption of time section
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing the electricity consumption of the plot during a rest period
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing the power usage of the plot during the work period
Account for the total daily electricity consumption
The proportional average number of (1);
representing the electricity consumption of the plot during a rest period
Account for the total daily electricity consumption
The ratio of (a) to (b).
3. The method of claim 1, wherein determining the place of employment and the place of residence in the target area based on the signaling data comprises:
projecting all the stay points on a Geographic Information System (GIS) map according to the signaling data;
the residence is determined in all the residence points corresponding to the residence analysis period, and the work place is determined in all the residence points corresponding to the work place analysis period.
4. The method of claim 3, wherein determining the residence or the work place among all the dwell points comprises:
determining the staying points with the staying time not less than a first staying time threshold value in all the staying points as alternative staying points;
determining a dwell point, of all the alternative dwell points, of which the proportion of the dwell time in the preset time interval is not less than a preset dwell probability threshold value, as a first effective dwell point;
and determining the residence point with the longest residence time in all the first effective residence points as the residence place or the working place.
5. The method of claim 1, wherein determining traffic travel volume (OD) data from the signaling data comprises:
clustering a plurality of base stations in the target area;
determining a staying track of the user equipment according to the signaling data recorded by the base station after the clustering;
determining a dwell point in the dwell track, the dwell time of which is not less than a second dwell time threshold value, as a second effective dwell point;
traversing all the second effective stop points, and determining a travel starting and ending point of the user equipment;
and counting the traffic travel (OD) data between the start and the end of the trip.
6. The method of claim 1, wherein determining a sample spreading factor based on the number of users and the signaling data comprises:
establishing a corresponding relation between the user number and the signaling data;
fitting a curve according to the corresponding relation;
and determining the sample expansion coefficient according to the fitted curve.
7. A population distribution analysis device, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for dividing a target area into a plurality of plots and acquiring power consumption data of each plot;
the identification module is used for identifying the type of the land parcel according to the electricity consumption data;
a second obtaining module, configured to obtain signaling data of the user equipment in the target area;
a first determining module, configured to determine a work place and a residence place in the target area according to the signaling data;
the second determining module is used for determining the number of the electricity consumers of the residential area according to the electricity consumption data;
a third determining module, configured to determine traffic travel (OD) data according to the signaling data;
a fourth determining module, configured to determine a sample expansion coefficient according to the user number and the signaling data;
and the fifth determining module is used for determining the population distribution characteristics of the target area according to the sample expansion coefficient and the traffic load (OD) data.
8. The apparatus of claim 7, wherein the identification module comprises:
the calculation unit is used for calculating the electricity utilization ratio of the land during the working period through a first formula and calculating the electricity utilization ratio of the land during the rest period through a second formula;
the first formula is:
the second formula is:
in that
＜
And is
＜
In the case of (3), determining the category of the land parcel as a characteristic land parcel of a residential area;
in that
＞
And is
Determining the type of the land parcel as a mixed region characteristic land parcel;
in that
And is
＜
Determining the type of the land parcel as a characteristic land parcel of a working land;
wherein the content of the first and second substances,
representing the power usage of the plot during the work period
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing the electricity consumption of the plot during a rest period
Account for the total daily electricity consumption
The ratio of (A) to (B);
representing the power usage of the plot during the work period
Account for the total daily electricity consumption
The proportional average number of (1);
representing the electricity consumption of the plot during a rest period
Account for the total daily electricity consumption
The ratio of (a) to (b).
9. The apparatus of claim 7, wherein the first determining module comprises:
the projection unit is used for projecting all the stay points on a Geographic Information System (GIS) map according to the signaling data;
a first determination unit for determining the residence in all the residence points corresponding to the residence analysis time period and determining the work place in all the residence points corresponding to the work place analysis time period.
10. The apparatus of claim 9, wherein the first determining unit comprises:
the first determining subunit is used for determining a dwell point, of which the dwell time is not less than a first dwell time threshold value, in all the dwell points as a candidate dwell point;
the second determining subunit is used for determining a stopping point, of all the alternative stopping points, of which the ratio of the stopping time to the preset time interval is not less than the preset stopping probability threshold value as a first effective stopping point;
and the third determining subunit is used for determining the dwell point with the longest dwell time in all the first effective dwell points as the residence place or the working place.
11. The apparatus of claim 7, wherein the third determining module comprises:
the processing unit is used for clustering a plurality of base stations in the target area;
a second determining unit, configured to determine a staying track of the user equipment according to the signaling data recorded by the clustered base station;
a third determining unit, configured to determine a dwell point in the dwell trajectory, where the dwell time is not less than a second dwell time threshold, as a second effective dwell point;
a fourth determining unit, configured to traverse all the second valid stop points, and determine a trip start and end point of the user equipment;
and the statistical unit is used for counting the traffic travel amount (OD) data between the start and the end of the trip.
12. The apparatus of claim 7, wherein the fourth determining module comprises:
the establishing unit is used for establishing the corresponding relation between the user number and the signaling data;
the fitting unit is used for fitting a curve according to the corresponding relation;
and the fifth determining unit is used for determining the sample expansion coefficient according to the fitted curve.
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