CN115934693A - Dynamic calculation method for regional real population - Google Patents
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Abstract
The invention discloses a dynamic calculation method for regional real population, which specifically comprises the following steps: s1, real population: including regular and floating populations, the actual population present that is active in the area is the real population. According to the technical scheme, the entrance registration inquiry is not needed, subjectivity caused by entrance registration or inquiry is avoided, data and actual conditions are prevented from entering and exiting, accuracy in data acquisition of the resident population is guaranteed, data accuracy of the resident population can be guaranteed, time cost and labor cost are saved, data based on ticket buying information is very accurate data collected by a public security department, and whether floating population leaves the jurisdiction or not is accurately judged by combining gate entering and exiting data of a traffic hub, so that the number of actual population in the jurisdiction can be accurately calculated.
Description
Technical Field
The invention relates to the technical field of regional population dynamic statistics, in particular to a regional real population dynamic calculation method.
Background
China has a large population, the demographic work is complicated, the definition of population attributes also has various statistical calibers, and generally, the actual population refers to all the populations in a certain area at a certain time point. According to the sixth regulation of the national institutes of residence registration regulations, the citizen should register as a permanent population in a place where the citizen frequently lives, and one citizen can register as a permanent population in only one place.
The floating population is a concept peculiar to China and is a product of a household registration system peculiar to China, roughly speaking, the floating population is a part of population which is resident from a household location to other places, but because of different time and space definitions, the range included by the floating population definition is different, so that the floating population can be defined as 'foreign population which resides in a certain place for half a year or more' in order to facilitate comparability of survey data of the floating population in various places and approach the international regulations on population migration management and research.
The population number is the basis of demographics, the accurate population number is mastered, the development planning of social economy is not only made, but also the analysis and research of population science are very important, the number of the population is large and small, the development degree of social division, the consumption level and the distribution proportion of accumulation and consumption are high, the market distribution and the scale can be influenced, so the social economy development is promoted or delayed, the conventional population statistical method in China needs to be registered or inquired in the home at present, the registration or inquiry of the home has strong subjectivity, data and actual conditions can be out of the home, the time cost and the labor cost of registration or inquiry of the home are high, the acquired population data are discrete points, the change trend of the population number cannot be timely and accurately analyzed and predicted, and therefore a corresponding regional real population dynamic calculation method is urgently needed to be provided to solve the problems.
Disclosure of Invention
The invention aims to: in order to solve the problems, a regional population dynamic calculation method is provided.
In order to achieve the purpose, the invention adopts the following technical scheme:
1. a regional real population dynamic calculation method specifically comprises the following steps:
s1, real population: the method comprises the following steps that (1) the method comprises a constant population and a floating population, wherein the number of the actual population moving in an area is a real population, and the real population is equal to the sum of the constant population and the floating population;
defining the real population further includes acquisition of data of the standing population and the floating population:
s11, acquiring data of the permanent population, checking registered population information including population household registration information, membership information and house address information through community policemen and grid members, and guaranteeing data quality by using the general survey experience of the past population in the information acquisition of the permanent population;
s12, obtaining floating population data, setting Internet of things sensing equipment in places where ticket booking information cannot be obtained according to the ticket booking information of a traffic hub and gate information entering and exiting the traffic hub, detecting and obtaining vehicle information and face information so as to judge an inflow population and an outflow population, merging and cleaning ticket purchasing information and gate information entering and exiting the traffic hub, subtracting the outflow population from the inflow population according to the fact that the floating population is equal to the inflow population, analyzing the data of the part of the floating population, setting the omnibearing Internet of things sensing equipment at the traffic hub based on the existing advanced Internet of things sensing equipment, capturing the face information without dead corners and analyzing the data, wherein the data are respectively stored in an inflow population table and an outflow population table in a machine room database of a city unit;
s2, storing a permanent population and a floating population: the method comprises the following steps of storing regular population data and floating population data tables, cleaning and checking the data of the two tables, eliminating dirty data, integrating various data and providing the data for calculation, and specifically comprises the following steps:
s21, developing based on a Mybaits framework;
s22, establishing a table and storing data;
when storing data, establishing a database and a table according to the local database structure of the source data, and then transmitting and storing the data into the local unit database;
s23, storing unstructured data;
s24, storing the data in a keyboard of a data integration platform, and performing duplicate checking and cleaning:
s3, various data sources are made into a mosaic-like modular operator in the system, the operator is assembled, and the assembled operator calculates the data according to a calculation formula designed by a background of a developer, namely according to the fact that the actual population is equal to the regular population and the floating population;
and S4, after the operator splicing is finished, the calculation in the S3 is automatically carried out, the calculation result is displayed after the calculation is finished, and a developer creates a log table in the server for recording all data changes and checking the log in the table.
Preferably, in step S4, the acquiring of unstructured data specifically includes:
the method comprises the following steps: carrying out serialization processing on the unstructured data to obtain serialized data;
step two: concatenating the serialized data with the index information for the unstructured data,
step three: storing a plurality of target data into a target structured data file.
Preferably, in the third step, when the plurality of target data corresponding to the plurality of unstructured data are merged and stored in the target structured data file, the target data are stored in the order of the designated order, that is, the order of the regular population and the floating population.
Preferably, in the third step, after the plurality of target data corresponding to the plurality of unstructured data are merged and stored in the target structured data file, the data need to be cleaned, and cleaning and sorting are performed according to the data acquisition time sequence, and the data acquisition time and the data acquisition place clearly reflect the flow direction of the floating population.
Preferably, in step S21, an sql session factor, that is, a session factory, is obtained through configuration information such as a Mybatis framework environment, the sql session, that is, a session is created by the session factory, an operation database needs to be performed through the sql session, an execution Executor interface operation database is customized on a Mybatis bottom layer, a Mapped state is a bottom-layer packaging object of the Mybatis framework, the Mapped state defines input parameters for sql, the Mapped state defines output results for sql, and the Mapped state maps the output results to java objects after sql is executed through the Mapped state.
Xml, that is, sql maps a file in which sql statements for operating the database are configured in step S21.
Preferably, in step S21, one sql in the xml file corresponds to one Mapped state unique, and the id of sql is the id of Mapped state.
Preferably, in step S21, mapping the input java object into sql before executing sql by MappedStatement, and inputting parameter mapping, i.e. parameter setting for preppedstatement in jdbc programming.
Preferably, in step S23, the unstructured data is data with irregular or incomplete data structure and no predefined data model, and the unstructured data includes images, audio, video, documents, custom objects, extensible markup language and hypertext markup language.
Preferably, in step S1, the permanent population is a population living in a local area for a long time, the population data of stable work and study is present in the local area, the floating population can be divided into an inflow population and an outflow population, the inflow population refers to a resident and a non-resident population coming to the area, the outflow population refers to a resident and a non-resident population living in other places away from the area, wherein the resident is a population with a local household, and the non-resident population includes a population without a local household and a foreign country.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
according to the technical scheme, when population statistics is carried out, the inquiry of entry registration is not needed, subjectivity of entry registration or inquiry is avoided, the data and actual situation entrance and exit are avoided, the accuracy of data acquisition of the standing population is guaranteed, the data accuracy of the standing population can be guaranteed, time cost and labor cost of entry registration or inquiry are saved, if the collected population data are discrete points, the change trend of the population quantity cannot be timely and accurately analyzed and predicted, the data based on ticket purchasing information is very accurate data collected by a public security department, the entrance and exit gate data of a traffic hub are combined, whether the floating population leaves the jurisdiction or not is accurately judged, the data identified by the human face is added by combining with camera shooting except the ticket purchasing information and the entrance and exit gate data, and the quantity of the actual population in the jurisdiction can be accurately calculated.
Drawings
FIG. 1 is a schematic diagram of a flow structure provided in accordance with an embodiment of the present invention;
fig. 2 is a schematic structural diagram for acquiring unstructured data 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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Referring to fig. 1-2, the present invention provides a technical solution: a regional real population dynamic calculation method specifically comprises the following steps:
s1, actual population: the method comprises the following steps that a standing population and a floating population are included, the number of actually existing population moving in an area is a real population, the real population is equal to the sum of the standing population and the floating population, the standing population is locally inhabited for a long time, population data for stable work and study are locally existed, the floating population can be divided into an inflow population and an outflow population, the inflow population refers to household and non-household populations coming to the area, the outflow population refers to household and non-household populations leaving the area to be inhabited to other areas, the household population is a population with local household, and the non-household populations include populations without local household and foreign households;
defining the real population further includes acquisition of data of the standing population and the floating population:
s11, acquiring data of the permanent population, checking and registering population information including population household registration information, membership information and house address information by a community policeman and a grid member, wherein in the information acquisition of the permanent population, the data quality is guaranteed by using the general survey experience of the past population for reference, and the accuracy of the data needs to be guaranteed in the process;
s12, obtaining floating population data, setting Internet of things sensing equipment at a high-speed intersection and a bus station in a place where ticket booking information cannot be obtained according to train, high-speed rail and airplane booking information and gate information of an airport of an access station, detecting and obtaining vehicle information and face information, and judging inflow and outflow population, and merging and cleaning ticket booking information and gate data of the access station, (1) obtaining ticket booking information of people by cooperation of civil aviation authorities of railway offices, wherein the ticket booking information comprises names, sexes, identity cards, a starting station, a destination station, passenger (flight) information, seat information and the like; the method comprises the following steps of 2, obtaining gate machine data of an identity card swiped in a site in cooperation with a railway station and an airport, 3, merging and cleaning the data, marking a label (0/1) for people going out, wherein 0 represents that ticket purchasing data is identical with the gate machine data, namely, a passenger purchases an airplane ticket and smoothly gets on the airplane to leave the area through the gate machine, 1 represents that the ticket purchasing data is not identical with the gate machine data, namely, the passenger does not retrieve the same data in the gate machine data after purchasing the airplane ticket, namely, the passenger does not smoothly leave the area of the jurisdiction, namely, the whole cleaning process for judging inflow and outflow data) ticket purchasing information and gate machine data can use the identity card number as a reference, and then the ticket purchasing information and the gate machine information of the same identity card number can be used as a basis for the person to leave the jurisdiction, for example: the method is characterized in that 15, namely, the person can be judged to leave the district according to the judgment, the floating population is equal to the inflow population minus the outflow population, the data of the floating population can be judged and analyzed according to the method, and then the method is based on the prior advanced Internet of things sensing equipment, after the omnibearing internet-of-things sensing equipment is arranged in a station place, human face information can be captured without dead angles and analyzed (training of a portrait algorithm is completed on an image processing server, a GPU server is provided with a graphic acceleration card and is specially used for training a neural network model for a deep learning algorithm, a large number of photos need to be fed to the algorithm to be classified, the algorithm can continuously modify model parameters in the process, the classification result and the actual situation are fitted as much as possible, the model is more accurate as the training turns are increased, then the trained human face vector parameters are led into a portrait recognition program, characteristic values of any photo can be extracted and processed, a synchronous task is arranged on another data server, the synchronous task is used for extracting all identity photos meeting requirements, the characteristic values are extracted through the portrait recognition program and then are associated with the identity card, the data are stored in a human database, when all the identity card photos are collected, any one photo can be extracted through the portrait application service, the characteristic values are compared with the data in a portrait database, the identity card database, the identity number of the person is found, and the identity number of the photos (the number) flows into a city class database, and the data of a province-class mark-book (rk) and a family database, and a family number (rk) are respectively extracted through a family number corresponding to flow-class data;
a face acquisition program is written in Java and deployed in the Internet of things acquisition equipment, automatic face characteristic value acquisition can be carried out on hardware equipment in part of the face acquisition program, and unstructured data are directly serialized and transmitted back to a city unit database for storage;
writing a face characteristic value acquisition program in Java, wherein in part of face acquisition hardware equipment, the equipment can only carry out photographing processing and transmits photos back to a database which is a unit, and developers need to apply the face characteristic value acquisition program written in Java to extract characteristic values of the photos;
s2, storing a permanent population and a floating population: storing the regular population data (rk _ czrk) and the floating population data (rk _ ldrk), cleaning and checking the data of the two tables, eliminating the dirty data, integrating various data and providing the data for calculation, and specifically comprising the following steps of:
s21, developing based on a Mybaits framework, programming SQL sentences, programming is quite flexible, any influence on the existing design of an application program or a database cannot be caused, the SQL is written in the XML, the coupling between the SQL and program codes is removed, unified management is facilitated, XML labels are provided, writing of dynamic SQL sentences is supported, and the SQL sentences can be reused;
● Mybatis configuration: xml, which is used as a global configuration file of Mybatis and is configured with information such as the running environment of Mybatis;
● Obtaining sqlsessenfactory, namely a session factory, through configuration information such as Mybatis environment and the like;
● A session factory creates sqlsession, namely a session, and the operation of a database needs to be carried out through the sqlsession;
an execution or Executor interface operation database is customized by the Mybatis bottom layer, and the execution or interface has two implementations, one is a basic Executor and the other is a cache Executor;
the Mapped State is also a bottom-layer packaging object of mybatis, and guarantees mybatis configuration information, sql mapping information and the like;
● The Mapped State executes input parameter definition on the sql, wherein the input parameter definition comprises Hashmap, basic type, pojo and execution;
● Defining an sql execution output result by the Mapped State element, wherein the sql execution output result comprises that a Hashmap, a basic type, a pojo and an executive map the output result to a java object after the sql is executed by the Mapped State element, and the mapping process of the output result is equivalent to the analysis processing of the result in the jdbc programming;
s22, establishing a table and storing data;
when storing data, establishing a database and establishing a table according to source data, namely local database structures of a railway station, an airport and the like, and transmitting and storing the data into a local unit database;
s23, storing unstructured data:
the unstructured data are data with irregular or incomplete data structures, a predefined data model is not available, the data are inconvenient to represent by a database two-dimensional logic table, the storage volume is reduced, and the pressure on a server is reduced;
the unstructured data comprises one of images, audio, video, documents, custom objects, extensible markup language and hypertext markup language;
oracle can store video data of less than 4GB by a BLOB type. (define blob field, use dbms _ lob packet);
the database is self-defined as byte array type (such as image, etc.), a program is used for converting the video into stream, the stream is written into a field data array, and the field data array is stored into the database;
and storing the path of the video file in a database, and calling the file content of the path by a program. (upload of data into disk space, storage of paths in database);
unstructured data such as video, audio, files, etc. may be stored in some NoSQL solutions;
s24, storing the data in the button, and performing duplicate checking and cleaning:
redundant duplicate records in the lookup table (multiple fields):
select*from vitaea
where(a.peopleId,a.seq)in(selectpeopleId,seqfromvitaegroup bypeopleId,seqhavingcount(*)>1)
inquiring peopleId (personnel ID (identity card number) in a table to generate data twice or more, deleting blank data and repeated data, automatically recording warehousing time for reasonably normal data by a system, automatically storing the time in the table in a field form without any operation, automatically generating an acquisition place when the data of various stations, airports and other places are acquired, adding the data according to information of the data acquisition place, automatically generating the data acquisition place according to data sources, for example, photos shot at Wuhan train stations, wherein the content of the field is the Han train station, the step of adding the field is table building, and the step of table building is explained in the step S22;
a data collection field;
in the process of cleaning the data, factors such as the acquisition time and the acquisition place of the data to be analyzed of the floating population data are important for the accuracy of the floating population data;
the keyboard is used as an end-to-end data integration platform, can extract (Extraction), load (Loading), fall lake (DataLakeInjection), perform various cleaning (cleaning), conversion (Transformation) and Blending (Blending) on various data sources, and support multidimensional online analytical processing (OLAP) and data mining (Datamining);
the data is cleaned in the button, part of face information acquired by the acquisition equipment is simultaneously transmitted back to the acquisition place and the acquisition time, and then the button is required to match the part of serialized data with the basic information of the 'person', so that complete floating population data can be generated;
s3, various data sources are made into mosaic-like modular operators in the system, (firstly, data are stored in a server, and a visualization platform is built, (namely, the visualization platform does not display specific data content on a platform page, only displays the names of the data sources, and builds various algorithms, so that algorithm formulas related to the patent are listed, algorithms and operators needed in the algorithms, and the operators are placed at proper positions in the algorithm formulas, namely, real population = regular population + floating population, the regular population and the floating population are operators;
s4, after the operator splicing is finished, automatic calculation is carried out, a calculation result is displayed after the calculation is finished, and a developer can create a log table in the server for recording all data changes and checking logs in the table;
specifically, as shown in fig. 1, the unstructured data may be obtained from a file, or may be obtained from a message, and the method specifically includes:
the method comprises the following steps: carrying out serialization processing on the unstructured data to obtain serialized data;
serialization is a mechanism for processing object streams, i.e., streaming the contents of an object, performing read/write operations on the streamed object, and also transmitting the streamed object between networks;
serialization realization method
When a Java object is written to a hard disk or transmitted to other computers on the network, we need to write the corresponding object into a byte stream by Java. Why does we not use a uniform format for this general operation? Without error, the concept of serialization of java has emerged here. The sub-class ObjectOutputStream class under Java's OutputStream class has a corresponding WriteObject (Object) in which the corresponding Object is required to implement a serialized interface of Java;
when a java ee related item is developed by using tomcat, after the tomcat is closed, an object in a corresponding session is stored on a hard disk, if we want to read the content in the corresponding session from the tomcat when the tomcat is restarted, the content stored in the session must be subjected to related serialization operation, and if the jdbc loading driver is deserialization, a character string is changed into the object;
some attributes of the class do not need to be serialized, and the object serialization is realized by the serialization and the deserialization, but it can be found that all the attributes of the whole object are serialized when in operation, so that the transient key can define some contents without storing the contents by the transient key: a private transition String title; at this time, the title attribute cannot be serialized;
step two: connecting the serialized data with the index information of the unstructured data, namely connecting the serialized data with the index information of the unstructured data through a main key 'identity card number', integrating the data under the same identity card number to obtain target data, wherein the index information can comprise file names, file types and file retrieval field information;
step three: storing a plurality of target data into a target structured data file;
specifically, as shown in fig. 2, in step three, when a plurality of target data corresponding to a plurality of unstructured data are merged and stored in the target structured data file, the target data are stored in the order of the regular population and the floating population, which are the designated orders.
Specifically, as shown in fig. 2, in step three, after a plurality of target data corresponding to a plurality of unstructured data are merged and stored in a target structured data file, the data need to be cleaned, and cleaning and sorting are performed according to the data acquisition time sequence, so that the data acquisition time and place can clearly reflect the flow direction of the floating population.
Specifically, as shown in fig. 1, in step S21, mapper.
Specifically, as shown in fig. 1, in step S21, one sql in the xml file corresponds to one Mapped state for exclusive use, and the id of the sql is the id of the Mapped state. Specifically, as shown in fig. 1, in step S21, mapping the input java object to sql before executing sql by MappedStatement, where the input parameter mapping is to set a parameter to the preppedstatement in jdbc programming.
Referring to fig. 1, how to dynamically calculate the real population in city a, for example, first, the definition of the real population, that is, the permanent population + floating population = real population, is made clear, and under this definition, data is acquired for the two aspects. On the basis, a server is installed in a government organization in city a, a database is installed in the server, and the operation of table building is required.
The permanent population:
the number of the standing population is obtained through the general population survey of the policemen every year, and the community policemen A grope the standing population data (rk _ czrk) of the city A through the visit. After data is collated, the policemen collate the personnel details into Excel through paper files, developers introduce the Excel into our table, namely an rk _ czrk table, and the table is used for storing the frequent population data in the city A in a government unit server. This data is hereinafter referred to as cz.
Floating population:
the number of the floating population needs to be obtained through two aspects, on one hand, the number is the places such as railway stations, airports and the like with real ticket purchasing information and real entrance and exit gate data, and in the places, whether ticket buyers leave the city A or not can be judged through matching of the ticket purchasing information and the entrance and exit gate information. Similarly, in this part of places, the ticket buyer can also be judged whether to enter city a or not according to the ticket buying information and the entrance and exit gate information. Then the outgoing population data lc1, incoming population data lr1 are available in this section. Both pieces of data will be stored in tables, i.e., the ingress mouth table (rk _ lrrk) and the egress mouth table (rk _ lcrk).
At bus stops, places where ticket buying information cannot be acquired such as expressway intersections, namely, people need to use face snapshot equipment to take a snapshot, the expressway intersections are provided with the face snapshot equipment at the places where the ticket is to be accessed, people leaving the A city can take a snapshot at the passage where the people leave the station, and the expressway intersections leaving the city are taken a snapshot by the camera, otherwise, people entering the A city can also be taken a snapshot by the camera. The data of the part of the snapshot is extracted through the face characteristic value, and population data, namely outflow population data lc2 and inflow population data lr2, are obtained. Both parts of the data will be stored in tables, i.e. the ingress mouth table (rk _ lrrk) and the egress mouth table (rk _ lcrk).
After the standing population data and the floating population data are obtained, the real population in the city a can be calculated according to a formula, namely the real population in the city a = cz + (lr 1+ lr 2) - (lc 1+ lc 2).
In summary, the method for dynamically calculating the real population in the area provided by this embodiment does not need to register and inquire the entrance when performing population statistics, avoids subjectivity of registration or inquiry of the entrance, avoids data coming in and going out of actual situations, and ensures accuracy in data acquisition of the standing population, so that data accuracy of the standing population can be ensured, time cost and labor cost of registration or inquiry of the entrance are saved, and if the acquired population data is a discrete point, a trend of population quantity change cannot be timely and accurately analyzed and predicted.
The previous description of the embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A regional real population dynamic calculation method is characterized by specifically comprising the following steps:
s1, real population: the method comprises the following steps that (1) the method comprises a constant population and a floating population, wherein the number of the actual population moving in an area is a real population, and the real population is equal to the sum of the constant population and the floating population;
defining the real population further includes acquisition of data of the standing population and the floating population:
s11, acquiring data of the permanent population, checking and registering population information including population household registration information, membership information and house address information by a community policeman and a gridder, and guaranteeing the data quality by using the general survey experience of the past population in the information acquisition of the permanent population;
s12, acquiring floating population data, setting Internet of things sensing equipment in places where ticket booking information cannot be acquired according to the ticket booking information of a traffic hub and gate information entering and exiting the traffic hub, detecting and acquiring vehicle information and face information so as to judge inflow and outflow population, merging and cleaning ticket buying information and gate information entering and exiting the traffic hub, subtracting the outflow population according to the fact that the floating population is equal to the inflow population, analyzing the data of the part of the floating population, and setting omnibearing Internet of things sensing equipment in the places of the traffic hub based on the existing advanced Internet of things sensing equipment to capture face information without dead corners and analyze the data, wherein the data respectively exist in an inflow population table and an outflow population table in a machine room database of a city-level unit;
s2, storing a permanent population and a floating population: the method comprises the following steps of storing regular population data and floating population data tables, cleaning and checking the data of the two tables, eliminating dirty data, integrating various data and providing the data for calculation, and specifically comprises the following steps:
s21, developing based on a Mybaits framework;
s22, establishing a table and storing data;
when storing data, establishing a database and a table according to a local database structure of source data, and transmitting and storing the data into a local unit database;
s23, storing unstructured data;
s24, storing the data in a data integration platform button, and performing duplicate checking and cleaning:
s3, various data sources are made into a mosaic-like modular operator in the system, the operator is assembled, and the assembled operator calculates the data according to a calculation formula designed by a background of a developer, namely according to the fact that the actual population is equal to the regular population and the floating population;
and S4, after the operator splicing is finished, the calculation in the S3 is automatically carried out, the calculation result is displayed after the calculation is finished, and a developer creates a log table in the server for recording all data changes and checking the log in the table.
2. The method according to claim 1, wherein the acquiring of the unstructured data specifically comprises:
the method comprises the following steps: carrying out serialization processing on the unstructured data to obtain serialized data;
step two: concatenating the serialized data with the index information for the unstructured data,
step three: storing a plurality of target data into a target structured data file.
3. The method as claimed in claim 2, wherein in step three, when the plurality of target data corresponding to the plurality of unstructured data are merged and stored in the target structured data file, the target data are stored in the order of the regular population and floating population.
4. The method for calculating the actual population dynamics of a region according to claim 2, wherein in step three, after a plurality of target data corresponding to a plurality of unstructured data are merged and stored in a target structured data file, the data need to be cleaned, and cleaning and sorting are performed according to the sequence of data acquisition time, and the data acquisition time and place clearly reflect the flow direction of the floating population.
5. The method of claim 1, wherein in step S21, an sql session factor, that is, a session factory, is obtained through configuration information such as Mybatis framework environment, and the like, the session factory creates an sql session, an operation database needs to be performed through the sql session, an execution Executor interface operation database is customized by Mybatis bottom, a Mapped state is a bottom-layer packaging object of the Mybatis framework, an input parameter definition is performed on sql by a Mapped state, an output result is defined on sql by the Mapped state, and the output result is Mapped into a java object after sql is executed by the Mapped state.
6. The method of claim 5, wherein in step S21, the mapper is an sql mapping file in which sql statements for operating the database are configured.
7. The method of claim 6, wherein in step S21, a sql is unique to a Mapped status in the mapper.
8. The method of claim 7, wherein in step S21, input java objects are mapped into sql before execution of sql by MappedStation, and parameters are set in jdbc programming.
9. A regional real population dynamic calculation method as claimed in claim 1, wherein in step S23, the unstructured data is data with irregular or incomplete data structure without predefined data model, and the unstructured data includes images, audio, video, documents, custom objects, extensible markup language and hypertext markup language.
10. The method as claimed in claim 1, wherein in step S1, the permanent population is a permanent residence in a local area, the permanent population has data about stable working and learning in the local area, the floating population can be divided into an incoming population and an outgoing population, the incoming population refers to a resident and a non-resident population living in the area, the outgoing population refers to a resident and a non-resident population living in other areas away from the area, the resident population is a population with a local household, and the non-resident population includes a population without a local household and a population with a foreign household.
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| CN117313981A (en) * | 2023-07-11 | 2023-12-29 | 厦门身份宝网络科技有限公司 | Dynamic urban village population analysis method, device, equipment and readable storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117313981A (en) * | 2023-07-11 | 2023-12-29 | 厦门身份宝网络科技有限公司 | Dynamic urban village population analysis method, device, equipment and readable storage medium |
| CN117313981B (en) * | 2023-07-11 | 2024-05-14 | 厦门身份宝网络科技有限公司 | Dynamic urban village population analysis method, device, equipment and readable storage medium |
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