CN114219379A - Resource matching evaluation method and system suitable for community service circle - Google Patents
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Abstract
The embodiment of the application provides a resource matching evaluation method and system suitable for a community service circle, wherein the method comprises the steps of determining target facility distribution data and target community geographic data; acquiring the facility distribution density of each community configuration facility according to the incidence relation between the target facility distribution data and the target community geographic data; determining population distribution density of each community resident group according to historical travel tracks of community residents, historical stay time in a community and historical travel frequency; and performing resource matching evaluation according to the correlation matching degree between the facility distribution density and the population distribution density. The implementation of the method can evaluate the accuracy of the resource matching.
Description
Technical Field
The application relates to the technical field of city management, in particular to a resource matching evaluation method and system suitable for a community service circle.
Background
The community service is advocated by local governments, is based on the community organization with the property of the base layer such as the street resident committee and the like, and is developed for meeting various requirements of community members and solving the community problems, thereby being an emerging cause with social welfare. The service capacity of community service facility network points in a community service circle is generally influenced by the walking distance of residents in one quarter, population space distribution relationship and the service scale of the facility network points, and at present, under the large background of optimization and upgrading of industrial structures and improvement of mediation and cure, how to scientifically and quantitatively evaluate the rationality and effectiveness of resource matching construction of the 'one quarter community service circle' becomes a problem to be solved urgently at present.
At present, although domestic scholars evaluate the construction quality and the service function of a community service circle by a questionnaire survey research means, the national scholars do not combine data analysis, lack quantitative and accurate evaluation on the 'one-quarter community service circle' and have the problem of low evaluation accuracy.
Disclosure of Invention
An object of the embodiments of the present application is to provide a resource matching assessment method and system suitable for a community service circle, so as to solve the technical problem in the prior art that the assessment accuracy is not high.
The embodiment of the application provides a resource matching evaluation method suitable for a community service circle, which comprises the following steps:
determining target facility distribution data and target community geographic data;
acquiring the facility distribution density of each community configuration facility according to the incidence relation between the target facility distribution data and the target community geographic data;
determining population distribution density of each community resident group according to historical travel tracks of community residents, historical stay time in a community and historical travel frequency;
and performing resource matching evaluation according to the correlation matching degree between the facility distribution density and the population distribution density.
In a second aspect, an embodiment of the present application further provides a resource matching evaluation system suitable for a community service circle, where the system includes a data acquisition module, a first calculation module, a second calculation module, and an evaluation module, where:
the data acquisition module is used for determining target facility distribution data and target community geographic data;
the first calculation module is used for obtaining the facility distribution density of each community configuration facility according to the incidence relation between the target facility distribution data and the target community geographic data;
the second calculation module is used for determining population distribution density of each community resident group according to the historical travel track of the community residents, the historical stay duration in the community and the historical travel frequency;
and the evaluation module is used for carrying out resource matching evaluation according to the correlation matching degree between the facility distribution density and the population distribution density.
In a third aspect, an embodiment of the present application further provides a readable storage medium, where the readable storage medium includes a program of a resource matching assessment method applicable to a community service circle, and when the program of the resource matching assessment method applicable to the community service circle is executed by a processor, the method implements the steps of the resource matching assessment method applicable to the community service circle.
As can be seen from the above, the resource matching evaluation method, system and readable storage medium suitable for the community service circle provided in the embodiments of the present application determine the facility distribution density of each community configuration facility through the association relationship between the target facility distribution data and the target community geographic data. And determining strong correlation between community facility service and resident travel behaviors according to the correlation matching degree between the facility distribution density and the population distribution density, and performing resource matching evaluation. At present, through according to community resident demand matching community facility service for resident's each item demand can satisfy in the community service circle, in the resource assessment degree of accuracy, avoids the use of resource extravagant, realizes the effective integration to community service circle resource.
Additional features and advantages of the present application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the present application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a flowchart of a resource matching evaluation method suitable for a community service circle according to an embodiment of the present application;
FIG. 2 is a graph illustrating facility distribution density for various community configured facilities provided by an embodiment of the present application;
fig. 3 is a schematic structural diagram of a resource matching evaluation system suitable for a community service circle according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Referring to fig. 1, fig. 1 is a flowchart of a resource matching evaluation method applicable to a community service circle in some embodiments of the present application. The method is exemplified by being applied to a computer device (the computer device may specifically be a terminal or a server, and the terminal may specifically be but is not limited to various personal computers, notebook computers, smart phones, tablet computers and portable wearable devices, the server may be an independent server or a server cluster composed of a plurality of servers), and the method includes the following steps:
step S100, determining target facility distribution data and target community geographic data.
The data field of the target facility distribution data includes information such as name, address, longitude and latitude, belonging area, belonging category, and the like, and the data field of the target community geographic data includes community name, community longitude and latitude information, and the like, which is not limited in the embodiment of the application.
Specifically, the computer device acquires initial data, preprocesses the acquired initial data based on a preset preprocessing mode, and then determines target facility distribution data and target community geographic data based on an obtained preprocessing result.
In one embodiment, the computer device employs preprocessing methods including, but not limited to, the following: the method includes the steps of data screening (for example, filtering out facilities outside a flood mountain area where the facilities belong), data classification duplication elimination (for example, classifying 310 small-scale data including bus stations, restaurants, laundries and the like into life services, health services, traffic services, sports and entertainment leisure services, catering services and cultural services), repeated data duplication elimination and the like, and the method is not limited in the embodiment of the application.
In an embodiment, the computer device may obtain the target facility distribution data and the target community geographic data through open data provided by an open location data service platform such as hundredths, extremely sea, and the like, and of course, a specific data obtaining manner is not limited to the above one, and the embodiment of the present application does not limit this.
And S101, obtaining the facility distribution density of each community configuration facility according to the incidence relation between the target facility distribution data and the target community geographic data.
Specifically, the computer device performs spatial clustering based on the association relationship between the distribution location of the facility and the geographic location of the community by using a pre-constructed spatial clustering model, so as to obtain the facility distribution density of each community-configured facility.
And S102, determining population distribution density of each community resident group according to the historical travel track of the community residents, the historical stay time in the community and the historical travel frequency.
Specifically, the computer device can acquire the historical travel track of community residents through the mobile phone communication data, and distinguishes people with different activity characteristics based on the historical travel track. In one embodiment, the population of residents in the range of one kilometer, the number of times of the residential sector, the residence time of the residential sector is less than one kilometer, and the like can be reflected, so that the diversified demands and the community service function positioning of the residents can be indirectly reflected.
And step S103, performing resource matching evaluation according to the correlation matching degree between the facility distribution density and the population distribution density.
Specifically, the computer device may perform resource matching evaluation based on a strong correlation with the resident travel behavior according to the degree of correlation matching between the facility distribution density and the population distribution density. Wherein, the management terminal can be further fed back to again to the resource assessment result of gained, and at this moment, the managers who is located management terminal side can be based on the resource assessment result of receiving, and the maturity that the community service circle was equipped with is clear and definite to use this as the basis, according to community resident demand matching community facility service, make each item demand of resident can satisfy in the community service circle, improve resident life happiness.
Therefore, according to the resource matching evaluation method applicable to the community service circle provided by the embodiment of the application, the facility distribution density of each community configuration facility is determined through the incidence relation between the target facility distribution data and the target community geographic data. And determining strong correlation between community facility service and resident travel behaviors according to the correlation matching degree between the facility distribution density and the population distribution density, and performing resource matching evaluation. At present, through according to community resident demand matching community facility service for resident's each item demand can satisfy in the community service circle, in the resource assessment degree of accuracy, avoids the use of resource extravagant, realizes the effective integration to community service circle resource.
In one embodiment, the step S100 of determining the target facility distribution data and the target community geographic data includes:
step S1000, acquiring initial facility distribution data and initial community geographic data, wherein data fields in the initial facility distribution data comprise facility names, regions and categories to which the facility names belong, and data fields in the initial community geographic data comprise community names and community longitude and latitude information.
Step S1001, based on a preset preprocessing mode, processing initial facility distribution data and initial community geographic data respectively to obtain corresponding preprocessing results, wherein the preprocessing mode comprises the steps of screening the region to which the facility belongs based on the longitude and latitude information of the region to which the facility belongs and classifying and removing the weight based on the type to which the facility belongs.
Specifically, the obtained initial facility distribution data and initial community geographic data may be set in a unified data storage set. While preprocessing, the computer device may traverse through various data fields included in the initial facility distribution data and the initial community geographic data. In the traversing process, the computer equipment performs classification and duplicate removal and screening of the regions based on the determined preprocessing rule; for example, when the computer device performs the belonging area screening, for example, taking "flood mountain area" as an example, if it is determined that the longitude and latitude information of the corresponding facility belonging area or community does not belong to the "flood mountain area" according to the currently traversed data field, the data corresponding to the facility is taken as invalid data, and the invalid data is deleted from the data storage set; when the classification deduplication is performed, the situation is particularly directed to the situation that repeated intersection exists in the original data. In one embodiment, the computer device may choose to reclassify 310 subclasses of raw data including bus stops, restaurants, laundromats, barbershops, banking outlets, etc., and briefly classify them into six classes of life services, health services, transportation services, sports, entertainment, dining services, and cultural services.
Step S1002, based on the obtained preprocessing result, determining corresponding target facility distribution data and target community geographic data.
In the embodiment, the obtained initial facility distribution data and the initial community geographic data are preprocessed to complete the screening, the removing of the invalid data and the weight and the classification, so that the data accuracy is guaranteed, and the evaluation efficiency is improved.
In one embodiment, in step S101, obtaining the facility distribution density of each community configured facility according to the association relationship between the target facility distribution data and the target community geographic data includes:
and step S1010, based on the geographic data of the target communities, performing spatial clustering on the distribution data of the target facilities to obtain the total number of the configured facilities respectively covered by each community.
Specifically, the computer device may perform spatial clustering on the target facility distribution data based on a preset spatial clustering model. In one embodiment, the types of spatial clustering models involved include: (1) giving the divided clusters; (2) clustering based on hierarchy; (3) density-based clustering; (4) grid-based clustering. In the current embodiment, spatial clustering is performed by using a hierarchical clustering model.
It should be noted that the purpose of hierarchical clustering is to assign data objects to a hierarchical structure. In the present embodiment, the assigned hierarchy may be further understood as based on the geographic distribution locations of the communities and the facility distribution locations of the facilities, clustering based on the degree of spatial coincidence between the geographic distribution locations and the facility distribution locations, and determining the configuration facilities respectively covered by each community and the total number of configuration facilities based on the association of the spatial locations.
Step S1011, for each community, obtaining the distribution density of the configuration facilities based on the total number of the covered configuration facilities and the area location range.
Specifically, for a corresponding community, the computer device performs a division calculation on the total number of the configuration facilities covered by the community and the regional location range of the community, and then determines the distribution density of the configuration facilities in the community based on the obtained division result. Of course, in the current embodiment, the determination of the distribution density of the configuration facilities in the corresponding community is not limited to the above manner, for example, the computer device may further perform a modification on the above division formula based on a weighting calculation manner, and the like, which is not limited in the embodiment of the present application.
In the above embodiment, the target facility distribution data is spatially clustered based on the target community geographic data, and the degree of spatial association between the geographic distribution positions of the communities and the facility distribution positions of the facilities is analyzed, so that the purpose of accurately identifying the configured facilities covered by each community is achieved, and the accuracy of the distribution density of the configured facilities is ensured.
In one embodiment, in step S102, determining population distribution density of each community resident group according to the historical travel track, the historical stay duration in the community, and the historical travel frequency of the community resident, includes:
step S1020, mobile phone communication data provided by a mobile phone communication service provider and travel data of each community are obtained, where the travel data includes travel origin-destination attribute information, and the attribute information includes location information and time information.
Specifically, the mobile communication refers to a communication mode for communicating between a mobile user and a fixed-point user or between mobile users, and the mobile phone communication data refers to data generated during communication between mobile phone users based on the above communication mode, which includes, but is not limited to, various signaling event data generated by a user's mobile phone in a mobile network, for example, location update data generated by power on and off, handover data when a base station location area is crossed, periodic location update data, traffic data generated by internet access of a mobile user, and the like. The travel data of each community includes, but is not limited to, travel routes of community residents, travel time starting points, travel time end points of arriving at destinations, geographic positions of travel places and the like.
And S1021, determining the historical travel track of the community residents according to the mobile phone communication data, and determining the historical stay duration of the residents in the community according to the historical travel track.
Specifically, it is assumed that the target community is covered by a plurality of mobile base stations, and the basic information of each mobile base station includes an identification field, a geographic location where the mobile base station is located, and a coverage area. Based on the embodiment, the computer device further determines the target mobile base stations respectively accessed to the mobile phone users at different time periods in the outgoing process of the mobile phone users according to the mobile phone communication data. Then, the computer device performs position association based on fields included in the basic information of the target mobile base station, for example, the geographic position of the mobile base station, and determines the historical travel track of the community residents based on the position association result.
In an embodiment, the determined historical travel track of the community residents may be further displayed in a thermodynamic diagram, and a plurality of travel tracks with similar longitude and latitude are divided into the same group, wherein the same group is marked by the same color or identification pattern, and different groups are marked by different patterns.
And step S1022, determining the historical travel frequency of community residents according to the travel origin-destination attribute information.
And S1023, identifying resident population according to the historical stay time and the historical trip frequency of the residents in the community, and determining the population distribution density of the resident population in each community based on the resident population statistical quantity.
Specifically, according to the historical stay time A and the historical trip frequency B of the target resident in the community, when the computer device determines that A is larger than a preset first threshold value and B is larger than a preset second threshold value, the computer device can determine that the target resident is in the community for a long time and frequently, and the target resident belongs to resident population. And when determining that A is smaller than a preset first threshold value and B is smaller than a preset second threshold value, determining that the target population is a floating population which does not reside in the community and does not belong to a resident population. In the present embodiment, of course, not limited to the above-mentioned resident population identification method, the computer device may also (1) perform statistical analysis on the face snapshot data based on the constructed portrait archive, and determine whether the user is a resident population by counting the frequency of days that the user appears in a preset period; (2) analyzing whether a user frequently appears in the community or not according to the change condition of the access base station based on the base station correspondingly accessed by the mobile phone number of the user in the community, so as to determine whether the user is a resident population or not; (3) the resident population is identified by combining the above modes, which is not limited in the embodiment of the present application.
In the embodiment, the resident population is identified according to the historical stay duration and the historical trip frequency of the residents in the community, and the population distribution density of the resident population in each community is determined based on the resident population statistical number, so that floating population screening is realized, and the accuracy of the population distribution density is guaranteed.
In one embodiment, in step S103, performing resource matching evaluation according to the degree of correlation matching between the facility distribution density and the population distribution density includes: obtaining travel data of each community, wherein the travel data comprise travel origin-destination attribute information, and the attribute information comprises position information and time information; according to the position information, the time information and the distribution positions of all the configured facilities in the community, counting a target travel origin-destination point pair and a travel amount of the corresponding home-trip configured facilities; determining resident activity information according to the travel origin-destination pairs and the travel quantity obtained through statistics, wherein the resident activity information comprises activity intensity and the number of residents corresponding to the activity intensity; and determining the correlation matching degree between the facility distribution density and the population distribution density, and performing resource matching evaluation according to the correlation matching degree and the resident activity information.
In one embodiment, the method further comprises: dividing the importance degree of the regional position range covered by each community according to the value of the distribution density of the facility, and sequencing the divided levels from low to high; distributing mark colors for the region position ranges, wherein the color depth of the mark colors is adapted to the arrangement sequence of the importance degrees corresponding to the region position ranges; when the regional position ranges covered by the communities are displayed in the city map, the marking colors are displayed in the corresponding regional position ranges, so that the facility distribution density of the configured facilities covered in the corresponding regional position ranges is displayed by utilizing the difference of the colors.
Referring to fig. 3, an embodiment of the present application further provides a resource matching evaluation system 300 suitable for a community service circle, where the system 300 includes a data obtaining module 301, a first calculating module 302, a second calculating module 303, and an evaluation module 304, where:
a data obtaining module 301, configured to determine target facility distribution data and target community geographic data.
The first calculating module 302 is configured to obtain the facility distribution density of each community configured facility according to the association relationship between the target facility distribution data and the target community geographic data.
The second calculating module 303 is configured to determine population distribution density of each community resident group according to a historical travel track of the community resident, a historical stay duration in the community, and a historical travel frequency.
And the evaluation module 304 is used for performing resource matching evaluation according to the correlation matching degree between the facility distribution density and the population distribution density.
In one embodiment, the data obtaining module 301 is further configured to obtain initial facility distribution data and initial community geographic data, where a data field in the initial facility distribution data includes a facility name, a region to which the facility belongs and a category to which the facility belongs, and a data field in the initial community geographic data includes a community name and community longitude and latitude information; respectively processing initial facility distribution data and initial community geographic data based on a preset preprocessing mode to obtain corresponding preprocessing results, wherein the preprocessing mode comprises screening of regions to which facilities belong based on latitude and longitude information of communities and classification duplication removal based on types to which the facilities belong; and determining corresponding target facility distribution data and target community geographic data based on the obtained preprocessing result.
In one embodiment, the first calculating module 301 is further configured to perform spatial clustering on the target facility distribution data based on the geographic data of the target communities to obtain the total number of configured facilities respectively covered by each community; and obtaining the facility distribution density of the configuration facilities based on the total number of the covered configuration facilities and the regional position range for each community.
In one embodiment, the first calculation module 301 is further configured to determine a historical travel track of a community resident according to the mobile phone communication data, and determine a historical stay duration of the community resident according to the historical travel track; determining the historical travel frequency of community residents according to the travel origin-destination attribute information; and identifying resident population according to the historical stay time and the historical trip frequency of the residents in the community, and determining the population distribution density of the resident population in each community based on the resident population statistical number.
In one embodiment, the evaluation module 304 is further configured to obtain travel data of each community, where the travel data includes attribute information of a travel origin-destination, and the attribute information includes location information and time information; according to the position information, the time information and the distribution positions of all the configured facilities in the community, counting a target travel origin-destination point pair and a travel amount of the corresponding home-trip configured facilities; determining resident activity information according to the travel origin-destination pairs and the travel quantity obtained through statistics, wherein the resident activity information comprises activity intensity and the number of residents corresponding to the activity intensity; and determining the correlation matching degree between the facility distribution density and the population distribution density, and performing resource matching evaluation according to the correlation matching degree and the resident activity information.
In one embodiment, the system 300 further comprises a display module, wherein:
the display module is used for dividing the importance degree of the regional position range covered by each community according to the value size of the facility distribution density and sequencing the divided grades from low to high; distributing mark colors for the region position ranges, wherein the color depth of the mark colors is adapted to the arrangement sequence of the importance degrees corresponding to the region position ranges; when the regional position ranges covered by the communities are displayed in the city map, the marking colors are displayed in the corresponding regional position ranges, so that the facility distribution density of the configured facilities covered in the corresponding regional position ranges is displayed by utilizing the difference of the colors.
The resource matching evaluation system suitable for the community service circle determines the facility distribution density of each community configuration facility through the incidence relation between the target facility distribution data and the target community geographic data. And determining strong correlation between community facility service and resident travel behaviors according to the correlation matching degree between the facility distribution density and the population distribution density, and performing resource matching evaluation. At present, through according to community resident demand matching community facility service for resident's each item demand can satisfy in the community service circle, in the resource assessment degree of accuracy, avoids the use of resource extravagant, realizes the effective integration to community service circle resource.
The embodiment of the present application provides a storage medium, and when being executed by a processor, the computer program performs the method in any optional implementation manner of the above embodiment. The storage medium may be implemented by any type of volatile or nonvolatile storage device or combination thereof, such as a Static Random Access Memory (SRAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), an Erasable Programmable Read-Only Memory (EPROM), a Programmable Read-Only Memory (PROM), a Read-Only Memory (ROM), a magnetic Memory, a flash Memory, a magnetic disk, or an optical disk.
The storage medium determines the facility distribution density of each community configuration facility according to the association relationship between the target facility distribution data and the target community geographic data. And determining strong correlation between community facility service and resident travel behaviors according to the correlation matching degree between the facility distribution density and the population distribution density, and performing resource matching evaluation. At present, through according to community resident demand matching community facility service for resident's each item demand can satisfy in the community service circle, in the resource assessment degree of accuracy, avoids the use of resource extravagant, realizes the effective integration to community service circle resource.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A resource matching evaluation method suitable for a community service circle is characterized by comprising the following steps:
determining target facility distribution data and target community geographic data;
acquiring the facility distribution density of each community configuration facility according to the incidence relation between the target facility distribution data and the target community geographic data;
determining population distribution density of each community resident group according to historical travel tracks of community residents, historical stay time in a community and historical travel frequency;
and performing resource matching evaluation according to the correlation matching degree between the facility distribution density and the population distribution density.
2. The method of claim 1, wherein determining the target facility distribution data and the target community geographic data comprises:
acquiring initial facility distribution data and initial community geographic data, wherein data fields in the initial facility distribution data comprise facility names, regions and categories to which the facility names belong, and data fields in the initial community geographic data comprise community names and community longitude and latitude information;
respectively processing the initial facility distribution data and the initial community geographic data based on a preset preprocessing mode to obtain corresponding preprocessing results, wherein the preprocessing mode comprises screening of regions to which the facilities belong based on latitude and longitude information of communities and classification and duplication removal based on types to which the facilities belong;
and determining corresponding target facility distribution data and target community geographic data based on the obtained preprocessing result.
3. The method according to claim 1, wherein the obtaining the facility distribution density of each community configured facility according to the association relationship between the target facility distribution data and the target community geographic data comprises:
based on the geographic data of the target communities, carrying out spatial clustering on the distribution data of the target facilities to obtain the total number of the configured facilities respectively covered by each community;
and obtaining the facility distribution density of the configuration facilities based on the total number of the covered configuration facilities and the regional position range for each community.
4. The method according to claim 1, wherein determining the population distribution density of each community resident group according to the historical travel track, the historical stay duration in the community and the historical travel frequency of the community resident comprises:
the method comprises the steps of obtaining mobile phone communication data provided by a mobile phone communication service provider and travel data of each community, wherein the travel data comprise attribute information of travel origin-destination points, and the attribute information comprises position information and time information;
determining the historical travel track of the community residents according to the mobile phone communication data, and determining the historical stay duration of the residents in the community according to the historical travel track;
determining the historical travel frequency of community residents according to the travel origin-destination attribute information;
and identifying resident population according to the historical stay time and the historical trip frequency of the residents in the community, and determining the population distribution density of the resident population in each community based on the resident population statistical number.
5. The method of claim 1, wherein performing resource matching assessment according to the degree of correlation match between the facility distribution density and the population distribution density comprises:
obtaining travel data of each community, wherein the travel data comprise travel origin-destination attribute information, and the attribute information comprises position information and time information;
counting a target travel origin-destination point pair and a travel amount of corresponding to the home-trip configuration facilities according to the position information, the time information and the distribution positions of the configuration facilities in the community;
determining resident activity information according to the travel origin-destination pairs and the travel quantity obtained through statistics, wherein the resident activity information comprises activity intensity and the number of residents corresponding to the activity intensity;
and determining the correlation matching degree between the facility distribution density and the population distribution density, and performing resource matching evaluation according to the correlation matching degree and the resident activity information.
6. The method according to any one of claims 1-5, further comprising:
dividing the importance degree of the regional position range covered by each community according to the value of the distribution density of the facility, and sequencing the divided levels from low to high;
distributing mark colors for the area position ranges, wherein the color depth of the mark colors is adapted to the arrangement sequence of the importance degrees corresponding to the area position ranges;
and when the regional position ranges covered by the communities are displayed in the city map, displaying the mark colors in the corresponding regional position ranges so as to display the facility distribution density of the configured facilities covered in the corresponding regional position ranges by utilizing the difference of the colors.
7. A resource matching evaluation system suitable for a community service circle is characterized by comprising a data acquisition module, a first calculation module, a second calculation module and an evaluation module, wherein:
the data acquisition module is used for determining target facility distribution data and target community geographic data;
the first calculation module is used for obtaining the facility distribution density of each community configuration facility according to the incidence relation between the target facility distribution data and the target community geographic data;
the second calculation module is used for determining population distribution density of each community resident group according to the historical travel track of the community residents, the historical stay duration in the community and the historical travel frequency;
and the evaluation module is used for carrying out resource matching evaluation according to the correlation matching degree between the facility distribution density and the population distribution density.
8. The system of claim 7, wherein the data obtaining module is further configured to obtain initial facility distribution data and initial community geographic data, wherein data fields in the initial facility distribution data include a facility name, a region and a category to which the facility belongs, and data fields in the initial community geographic data include a community name and community longitude and latitude information; respectively processing the initial facility distribution data and the initial community geographic data based on a preset preprocessing mode to obtain corresponding preprocessing results, wherein the preprocessing mode comprises screening of regions to which the facilities belong based on latitude and longitude information of communities and classification and duplication removal based on types to which the facilities belong; and determining corresponding target facility distribution data and target community geographic data based on the obtained preprocessing result.
9. The system of claim 7, wherein the first computing module is further configured to perform spatial clustering on the target facility distribution data based on the target community geographic data to obtain a total number of configured facilities respectively covered by each community; and obtaining the facility distribution density of the configuration facilities based on the total number of the covered configuration facilities and the regional position range for each community.
10. A readable storage medium, wherein the readable storage medium includes a program for a resource matching assessment method applicable to a community service circle, and when the program for the resource matching assessment method applicable to the community service circle is executed by a processor, the steps of the method recited in any one of claims 1 to 6 are implemented.
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