CN120724040A - Method, device, apparatus, medium and program product for demographic statistics - Google Patents
Method, device, apparatus, medium and program product for demographic statisticsInfo
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Abstract
The present disclosure relates to a demographic method, apparatus, device, medium, and program product in the field of communication technology. The method comprises the steps of obtaining a first boundary vertex coordinate set of a minimum polygon capable of covering a discrete base station according to a list set of the discrete base station to obtain a regional polygon boundary, performing outer expansion on the regional polygon boundary based on a polygon outer expansion algorithm to obtain a second polygon boundary vertex coordinate set, obtaining a third polygon boundary vertex coordinate set by eliminating boundary crossing points, obtaining the number of users on a coverage area of a specified base station according to the third polygon boundary vertex coordinate set through secondary filtering of a spatial index algorithm and combining real-time user position data.
Description
Technical Field
The present disclosure relates to the field of communications technologies, and in particular, to a demographic method, apparatus, device, medium, and program product.
Background
Population flow management is critical to the identification of the flowing population, and traditional methods generally comprise population census, checkpoint statistics, sampling prediction and the like, but are limited by specific factors such as manpower, position and the like, and have the defects of universality, timeliness and accuracy.
With the rapid development of new digital technologies such as cloud computing, big data, artificial intelligence and the like, methods based on mobile phone signaling data, dynamic face recognition and the like are widely applied. Although the operator position signaling data has the advantages of wide coverage area, high user preservation, strong data continuity and the like, the position signaling has the non-negligible problem that the positioning accuracy of the position signaling data is poor. The problem can lead to inaccurate regional population identification, and particularly for regions with smaller areas such as scenic spots, markets and the like, the identification statistical error can be more serious, and the application and landing effects of the large data of the positions are affected.
In order to solve the problems, the invention provides a real-time regional population identification method based on base station industrial parameter data, which supports regional population identification based on base stations (non-regional boundaries) and accurate regional population identification based on regional boundaries on the premise of ensuring efficiency by a boundary generation algorithm and a regional effective base station coverage algorithm.
Disclosure of Invention
To solve the above technical problems, embodiments of the present disclosure provide a demographic method, apparatus, device, computer storage medium, and computer program product, which implement accurate regional population identification.
In a first aspect of embodiments of the present disclosure, there is provided a method of demographics, the method comprising:
According to the list set of the discrete base stations, a first boundary vertex coordinate set of the minimum polygon which can cover the discrete base stations is obtained, and a regional polygon boundary is obtained;
Performing outer expansion on the polygon boundary of the region based on a polygon outer expansion algorithm to obtain a second polygon boundary vertex coordinate set;
obtaining a third polygon boundary vertex coordinate set by eliminating boundary crossing points;
and obtaining the number of users in the coverage area of the appointed base station through secondary filtering of a spatial index algorithm and combining with real-time user position data according to the third polygon boundary vertex coordinate set.
In a second aspect of embodiments of the present disclosure, there is provided a method of demographics, the method comprising:
Determining a spatial coverage boundary of a base station, wherein the base station comprises an omni-base station and a directional base station;
Determining an area effective base station based on a space screening algorithm of the multidimensional space point index;
and determining the number of real-time users in the effective base station of the area based on the spatial index algorithm and the real-time position data of the users.
A third aspect of embodiments of the present disclosure provides a demographic device comprising:
The first module is configured to obtain a first boundary vertex coordinate set of a minimum polygon capable of covering the discrete base station according to the list set of the discrete base station, and obtain a regional polygon boundary;
The second module is configured to perform expansion on the polygon boundary of the area based on a polygon expansion algorithm to obtain a second polygon boundary vertex coordinate set;
A third module configured to obtain a third polygon-boundary vertex coordinate set by eliminating boundary intersections;
And the statistical module is configured to obtain the number of users in the coverage area of the appointed base station through secondary filtering of a spatial index algorithm and combination of real-time user position data according to the third polygon boundary vertex coordinate set.
In a fourth aspect of embodiments of the present disclosure, there is provided a demographic device comprising:
a boundary module configured to determine a spatial coverage boundary of a base station, wherein the base station comprises an omni-base station and a directional base station;
the effective module is configured to determine an area effective base station based on a space screening algorithm of the multidimensional space point index;
And the comparison module is configured to determine the number of real-time users in the effective base station of the area based on the spatial index algorithm and the real-time position data of the users.
In a fifth aspect of embodiments of the present disclosure, there is provided an electronic device, including:
at least one processor;
a memory for storing the at least one processor-executable instruction;
wherein the at least one processor is configured to execute the instructions to implement the method of any one of the first or second aspects above.
A sixth aspect of embodiments of the present disclosure provides a computer readable storage medium, which when executed by a processor of an electronic device, causes the electronic device to perform the method of any one of the first or second aspects described above.
A seventh aspect of embodiments of the present disclosure provides a computer program product comprising a computer program which, when executed by a processor, performs the steps of the method of demographics of any one of the first or second aspects described above.
The embodiment of the disclosure provides a real-time regional population identification method based on base station industrial parameter data, which not only supports regional population identification of non-regional boundaries, but also supports accurate regional population identification based on regional boundaries on the premise of ensuring efficiency by a boundary generation algorithm and a regional effective base station coverage algorithm.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a flow diagram of a demographic method provided by an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of an algorithm for obtaining regional polygon boundaries in step S111 of a demographic method according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a boundary flare invalidation flare point provided in an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of a region boundary after elimination of boundary crossing points provided by an embodiment of the present disclosure;
FIG. 5 is a flow chart of yet another demographic method provided by an embodiment of the present disclosure;
fig. 6 is a schematic coverage area diagram of a directional base station according to an embodiment of the disclosure
Fig. 7 is a schematic flow chart of determining an area effective base station according to an embodiment of the present disclosure;
FIG. 8 is a schematic diagram of a demographic device provided in an embodiment of the present disclosure;
FIG. 9 is a schematic diagram of a further demographic device provided in an embodiment of the present disclosure;
Fig. 10 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure;
Fig. 11 is a schematic structural diagram of an exemplary computer system according to an embodiment of the present disclosure.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein, and it is apparent that the embodiments in the specification are only some, rather than all, of the embodiments of the present disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.
It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.
With the continuous enhancement of national economy activity, traffic is increasingly convenient, and trans-regional population flow is normal. The management of the flow of people is the foundation for promoting the continuous healthy development of economy and the harmony and stability of society. Population flow management is critical to the identification of the flowing population, and traditional methods generally comprise population census, checkpoint statistics, sampling prediction and the like, but are limited by specific factors such as manpower, position and the like, and have the defects of universality, timeliness and accuracy.
With the rapid development of new digital technologies such as cloud computing, big data, artificial intelligence and the like, methods based on mobile phone signaling data, dynamic face recognition and the like are widely applied. Although the operator position signaling data has the advantages of wide coverage area, high user preservation, strong data continuity and the like, the position signaling has the non-negligible problem that the positioning accuracy of the position signaling data is poor. The problem can lead to inaccurate regional population identification, and particularly for regions with smaller areas such as scenic spots, markets and the like, the identification statistical error can be more serious, and the application and landing effects of the large data of the positions are affected.
In order to solve the above problems, the embodiments of the present disclosure provide a real-time regional population identification method based on base station industrial parameter data, which not only supports regional population identification based on base stations (non-regional boundaries) but also supports precise regional population identification based on regional boundaries on the premise of ensuring efficiency by using a boundary generation algorithm and a regional effective base station coverage algorithm, thereby realizing precise regional population identification and improving calculation efficiency.
Before explaining the scheme of the present disclosure, for the convenience of understanding, terms involved in the embodiments of the present disclosure are explained.
The base station engineering parameters are called base station engineering parameters, and are important parameters of the mobile communication base station antenna in maintenance and network optimization. These parameters include longitude and latitude, altitude, azimuth, mechanical downtilt, etc., which have a decisive influence on the electromagnetic coverage of the base station.
Azimuth is an important concept in the engineering parameters of a base station, and refers to the pointing angle of an antenna of the base station, wherein the base station is usually used as an origin, the north direction of the antenna is 0 degree or 360 degrees, and then the angle of the direction pointed by the antenna is measured clockwise.
The area effective base station is characterized in that an electromagnetic coverage space of the base station and an area circling space of the area are intersected, and the area ratio of the intersection area to the circling area is larger than a threshold value alpha, wherein alpha is a constant which is defined to be larger than 0 and smaller than 1.
The demographic method provided by the embodiment of the disclosure depends on the real-time position data of the user and the service Shang Ji station industrial parameter data, and can support the region demographics with only the base station list and without boundary and also can support the region demographics with only the region boundary and without the base station list.
Methods, apparatus, devices, computer storage media, and computer program products for demographics provided by embodiments of the present disclosure are described below in conjunction with fig. 1-11.
Fig. 1 is a flowchart of a demographic method provided by an embodiment of the present disclosure, as shown in fig. 1, for a demographic scene of an existing regional base station list, in order to avoid association matching of a full amount of data, an embodiment of the present disclosure provides a borderless regional demographic method, which includes:
S111, according to a list set of the discrete base stations, a first boundary vertex coordinate set of a minimum polygon capable of covering the discrete base stations is obtained, and a regional polygon boundary is obtained;
defining a list set of discrete base stations as:
Wherein, the For the object containing the longitude and latitude information of the base station, lng is the longitude of the base station cell, and lat is the latitude of the base station cell.
In one embodiment, fig. 2 is an algorithm schematic diagram of obtaining regional polygon boundaries in step S111 of a demographic method according to an embodiment of the present disclosure, where, as shown in fig. 2, step S111 includes:
S1111, finding out a point with the largest latitude and the smallest longitude according to the list set of the discrete base stations, and marking the point as a point p 1;
for the list set of known discrete base stations, finding out the point with the largest latitude and the smallest longitude, and recording the point as the point ;
As illustrated in the upper left corner of fig. 2, the point with the greatest latitude and the smallest longitude is point a, and point a is denoted as p 1.
S1112, at the start pointTaking the point as the origin, making rays in the forward direction, scanning clockwise, finding out the point scanned when the rotation angle is minimum, and recording as;
As shown in the upper left corner of FIG. 2, the point B is the point B scanned when the minimum rotation angle is found by taking the point A as the origin and taking rays in the forward direction and scanning clockwise, and is recorded as。
S1113 self-primingBeginning withAs the origin, toThe direction is irradiated, scanned clockwise, and the scanning points with the smallest rotation angle are searched one by one and recorded asPoint until finding out the starting pointUntil now, n is a natural number;
as illustrated in the upper right hand corner of fig. 2, to The point is the origin, in order toTaking the B point as an origin, taking the AB direction as an origin, scanning clockwise, and taking the scanned point as the C point when the minimum rotation angle is found, and recording asA dot;
As illustrated in the lower left corner of fig. 2, to The point is the origin, in order toTaking the C point as the origin, taking the BC direction as the origin, scanning clockwise, and taking the scanned point as the D point when the minimum rotation angle is found, and recording asA dot;
And so on until the starting point is found Until the scan finds the point a, as shown in the lower right hand corner of fig. 2.
S1114, sequentially recording the points retrieved in the search process, and recording them as a first boundary vertex coordinate set containing the minimum polygon boundary of the base station:。
S112, performing expansion on the polygon boundary of the region based on a polygon expansion algorithm to obtain a second polygon boundary vertex coordinate set;
performing proper expansion on the regional polygon boundary generated in the step S111 according to a polygon expansion algorithm to generate a second polygon boundary vertex coordinate set:
。
S113, obtaining a third polygon boundary vertex coordinate set by eliminating boundary crossing points;
fig. 3 is a schematic diagram of a boundary expansion invalid expansion point provided by an embodiment of the present disclosure, as shown in fig. 3, after the region polygon boundary is expanded, there may be a boundary crossing condition, and the crossing boundary is not friendly to the spatial index calculation, so that the crossing boundary condition is eliminated.
Illustratively, step S113 includes:
s1131, splitting the boundary of the second polygon boundary vertex coordinate set into an end-to-end directed line segment set ;
I.e. the second polygon boundary vertex coordinate setIs split into end-to-end directed segment sets;
S1132, sequentially calculating the intersection points of all the directed line segments to form an ordered intersection point set;
S1133, forming a new end-to-end directed line segment set according to the generated intersection point set;
S1134, traversing the directed line segment set in turnAnd taking the effective expansion points into an expansion effective point set to obtain a third polygon boundary vertex coordinate set.
Illustratively, step S1134 includes:
S11341, traversing the directed line segment set in turn Calculate each pointThe number of times of the starting point is recorded as the effective expansion point, wherein the number of times of the starting point is more than 1;
Traversing in turn Calculate each pointThe number of times as the starting point indicates that a point is an effective flare point if the number of times as the starting point is greater than 1, and indicates that a point is an ineffective flare point if the number of times as the starting point is greater than 1, i.e.Intersection points of the middle directional line segments;
Traversing in turn A set of starting points for each line segmentIf (3)Is a valid point of the expansion, the point is included in the final set of valid points of the expansion, ifThe point is a flare nulling point and then all directed line segments following the point are ignored until the next directed line segment starting at the point.
S11342, incorporating the valid expansion points into the expansion valid point set to obtain a third polygon boundary vertex coordinate set.
And taking all the effective expansion points into an expansion effective point set, and finally obtaining an expansion effective point set to obtain a third polygon boundary vertex coordinate set, namely, a vertex coordinate set of an expansion polygon covering the discrete base station point positions.
The outer expansion boundary may also be generated by the method of the center of the region and the furthest coverage radius, illustratively when eliminating the intersection.
Fig. 4 is a schematic diagram of a region boundary after the boundary crossing point is eliminated, and as shown in fig. 4, the outermost boundary is the region boundary effect after the boundary crossing point is finally eliminated.
And S114, obtaining the number of users in the coverage area of the appointed base station through secondary filtering of a spatial index algorithm and combination of real-time user position data according to the third polygon boundary vertex coordinate set.
And the third polygon boundary vertex coordinate set obtained in the step S113 is combined with the secondary filtering of the spatial index algorithm and the real-time user position data, so that the number of users in the coverage area of the appointed base station can be obtained in real time and efficiently.
In the embodiment of the disclosure, for the region of the known base station list, a region boundary generation method is provided, based on the algorithm, region screening errors caused by region circling are avoided, and by introducing space index calculation through the generated region boundary, the association operation of the full user position data and the known base station list can be avoided, so that the effects of improving the calculation efficiency and reducing the calculation resource cost are achieved.
Fig. 5 is a flowchart of another demographic method according to an embodiment of the present disclosure, and in order to determine the accuracy of regional population screening for a scene of an existing regional boundary, a precise regional population identification method based on base station industrial parameters is provided, where base station industrial parameters required by the method are shown in table 1.
TABLE 1
As shown in fig. 5, the method includes:
S511, determining the space coverage boundary of the base station, wherein the base station comprises an omni-base station and a directional base station.
The base stations are divided into a directional base station and an omnidirectional base station, the coverage angle of an antenna of the omnidirectional base station is 360 degrees, and the coverage boundary of the omnidirectional base station can be regarded as the projection of a cylinder with the base station position as the center and the coverage radius of the base station on the surface of the earth.
Fig. 6 is a schematic coverage diagram of a directional base station according to an embodiment of the present disclosure, where, as shown in fig. 6, the coverage boundary of the directional base station may be approximately the triangular range as shown in fig. 6. The procedure for determining the boundary of the spatial coverage of the directional base station is as follows:
S5111, obtaining the space coverage boundary angle of the base station cell according to the azimuth angle and the coverage angle of the base station cell.
First, a coordinate system is established by taking longitude and latitude of a base station as vertexes, the direction of an X axis is defined as the forward direction, and the direction of a Y axis is defined as the forward direction.
And calculating the space coverage boundary angle of the base station cell according to the azimuthAngle azimuth angle and the degRange base station cell coverage angle, wherein LEFTDEGREE and RIGHTDEGREE are respectively the degrees of the included angles between the two boundaries of the sector of the base station cell and the positive direction of the Y axis. The calculation formula is as follows:
Wherein, the AndThe degrees of the included angles between the two boundaries of the sector of the base station cell and the positive direction of the Y axis (namely the positive north direction) are respectively shown.
S5112, according to the space coverage boundary angle of the base station cell, the coordinates of the other two vertexes of the coverage triangle boundary of the base station cell are obtained.
One vertex of the triangle boundary covered by the base station cell is the base station, and the coordinates of the other two vertices of the triangle boundary covered by the base station cell are calculated according to LEFTDEGREE and RIGHTDEGREE, and the coordinates are respectively calculatedAndSubstituting the following formula to obtain longitude and latitude coordinates of the other two vertexes of the triangle boundary covered by the base station cell.
S5113, according to the vertex coordinates of the coverage triangle boundary of the base station cell, the space coverage area of the base station cell is obtained.
And calculating the coverage area of the base station cell according to the base station cell coverage triangle boundary vertex coordinates obtained in the step S5112.
S512, determining the regional effective base station based on a spatial screening algorithm of the multidimensional space point index.
Fig. 7 is a flowchart of determining an area effective base station according to an embodiment of the present disclosure, as shown in fig. 7, S512 includes the following steps:
S5121, judging whether the area is polygonal;
If the target area is a polygon, calculating a center point p of the polygon, and if the target area is a circle, omitting the step;
S5122, determining a space expansion area of the target area;
if the target area is polygonal, sequentially calculating the distance between the boundary vertex and the center point p, and taking the farthest distance d;
s5123, screening base stations in a space expansion area;
The spatial screening algorithm based on the multidimensional spatial point index is based on a base station set stations contained in a circular area with a center point p (if the base station set is a circular area), which is taken as a center, and d+r (if the base station set is a circular area, d is a radius of the circular area) as a radius.
S5124, the coverage area and the area of the base station are calculated in sequence;
Traversing stations sets according to a base station coverage calculating method, sequentially calculating coverage space boundaries baseStaionBoundary of each base station, and calculating coverage space areas baseStationArea of the base stations based on the boundaries;
s5125, sequentially calculating the space intersection area of the coverage area of the base station and the target area;
Traversing stations the set, and sequentially calculating the area intersectionArea of the intersection area of each base station and the target area.
S5126, sequentially calculating the ratio of the intersection area to the area of the base station;
Ratio= intersectionArea/baseStationArea was calculated.
S5127, reserving the base station with the ratio larger than a preset threshold value.
If ratio > = a, reserving the base station, and if ratio < a, removing the base station, wherein a is a preset threshold.
S513, determining the number of real-time users in the effective base station of the area based on the spatial index algorithm and the real-time position data of the users.
Based on the spatial index algorithm spatial index and the user real-time position data, the number initiatory _result of users in the circular area with the point p (if the circular area is the center of the circular area) and d+r (if the circular area is the radius of the circular area) as the radius, which are obtained in the step S512 by using the steps S5121-S5123.
It will be appreciated that a spatial index, which is a data structure used to accelerate the querying of spatial data, builds an index structure by organizing and arranging spatial data according to certain rules, so that we can quickly locate spatial objects related to the query conditions without traversing all the data.
Further, comparing the base station codes in the real-time position data of the users in the area effective base station with the base station codes in the area effective base station industrial parameters, reserving the users with consistent comparison results, obtaining the number of real-time users in the area effective base station, namely traversing the real-time position data of initiatory _result users, comparing the base station codes in the position data with the base station codes in the area effective base station industrial parameters, reserving the users if the base station codes are consistent, and eliminating the users if the base station codes are inconsistent. And finally, the reserved user set is the accurate real-time population in the area.
In the embodiment of the disclosure, a precise regional population identification algorithm based on base station industrial parameters is proposed for a region with a known regional boundary. Firstly, the algorithm calculates the coverage boundary and the space coverage area of the base station through the base station industrial parameters, provides a reference basis for accurate population identification behind the algorithm, and secondly, the algorithm can calculate the base station of the effective coverage area in the area peripheral range based on the data of the coverage boundary, the coverage space area of the base station, the known area boundary and the like of the base station. And finally, comparing the position data of the regional population with the effective base stations to obtain an accurate regional population identification result. According to the scheme, the base station antennas which are arranged in the area and are adjacent to the area boundary and oriented outside the area in azimuth angle can be eliminated, and the base station antennas which are arranged outside the self-defined area and are adjacent to the area boundary and oriented in the area direction can be introduced. The method and the device avoid the situation that people in the area are not screened by the area because the people in the area are connected with the base station outside the area to a certain extent, and also avoid the situation that people outside the base station are screened by the self-defined area because the people outside the base station are connected with the base station inside the area, thereby improving the screening precision of regional crowd.
The embodiment of the disclosure realizes efficient and accurate identification of regional population under two scenes of regional boundary and non-regional boundary based on the boundary generation algorithm and the regional effective base station screening algorithm. The technical scheme has the advantages of strong real-time performance, high coverage rate, good continuity and good dynamic performance when realizing regional user statistics. The method has higher application value and social value in aspects of demographics, monitoring of specific areas, understanding of population flow rules and modes, such as emergency population flow monitoring and early warning, and the like, and the method can be used for identifying and analyzing population attributes by combining other data sources, such as socioeconomic attributes, commuter travel characteristics, and the like.
The foregoing is only illustrative of the preferred embodiments of the invention, and it will be appreciated by those skilled in the art that modifications, adaptations and variations may be made without departing from the principles of the invention, and are intended to be within the scope of the invention.
Fig. 8 is a schematic structural diagram of a demographic device according to an embodiment of the disclosure, as shown in fig. 8, the demographic device 800 includes:
A first module 801 configured to obtain a first boundary vertex coordinate set of a smallest polygon capable of covering the discrete base station according to the list set of the discrete base station, and obtain a regional polygon boundary;
A second module 802 configured to perform, based on a polygon expansion algorithm, expansion of the region polygon boundary to obtain a second polygon boundary vertex coordinate set;
A third module 803 configured to obtain a third polygon-boundary vertex coordinate set by eliminating boundary intersections;
The statistics module 804 is configured to obtain the number of users in the coverage area of the specified base station according to the third polygon boundary vertex coordinate set through secondary filtering of the spatial index algorithm and combining with real-time user position data.
In some embodiments, the first module 801 comprises:
The first searching module is configured to search out a point with the largest latitude and the smallest longitude according to the list set of the discrete base stations, and the point is recorded as a point p 1;
a second search module configured to start at Taking the point as the origin, making rays in the forward direction, scanning clockwise, finding out the point scanned when the rotation angle is minimum, and recording as;
A third search module configured to be self-containedBeginning withAs the origin, toThe direction is irradiated, scanned clockwise, and the scanning points with the smallest rotation angle are searched one by one and recorded asPoint until finding out the starting pointUntil, where n is a natural number;
A recording module configured to sequentially record the points retrieved in the search process, as a first boundary vertex coordinate set containing the minimum polygon boundary of the base station: 。
in some embodiments, the third module 803 includes:
A splitting module configured to split the boundary of the second polygon boundary vertex coordinate set into an end-to-end directed line segment set ;
The intersection module is configured to sequentially calculate the intersection points of all the directed line segments to form an ordered intersection point set;
The collection module is configured to form a new end-to-end directed line segment collection according to the generated intersection point collection;
A traversing module configured to sequentially traverse the set of directed line segmentsAnd taking the effective expansion points into an expansion effective point set to obtain a third polygon boundary vertex coordinate set.
In some embodiments, the traversal module comprises:
A computation module configured to traverse the set of directed line segments in sequence Calculate each pointThe number of times of the starting point is recorded as the effective expansion point, wherein the number of times of the starting point is more than 1;
And the collection module is configured to incorporate the valid expansion points into the expansion valid point collection to obtain a third polygon boundary vertex coordinate collection.
Fig. 9 is a schematic structural diagram of yet another demographic device provided in an embodiment of the disclosure, where, as shown in fig. 9, the demographic device 900 includes:
A boundary module 901 configured to determine a spatial coverage boundary of a base station, wherein the base station comprises an omni-base station and a directional base station;
An effective module 902 configured to determine an area effective base station based on a spatial screening algorithm of the multidimensional spatial point index;
a comparison module 903 configured to determine the number of real-time users in the area effective base station based on the spatial index algorithm and the user real-time location data.
In some embodiments, the border module 901 includes:
a coverage module configured to obtain a spatial coverage boundary angle of the base station cell according to the azimuth angle and the base station cell coverage angle;
the vertex module is configured to obtain coordinates of two other vertices of the coverage triangle boundary of the base station cell according to the space coverage boundary angle of the base station cell;
and the area module is configured to obtain the space coverage area of the base station cell according to the vertex coordinates of the coverage triangle boundary of the base station cell.
In some embodiments, the active module 902 includes:
A determining module configured to determine a spatial expansion area of the target area;
A screening module configured to screen base stations within the spatial extension area;
the range module is configured to sequentially calculate the coverage area and the area of the base station;
An intersection module configured to sequentially calculate a spatial intersection area of a coverage area of the base station and the target area;
the ratio module is configured to sequentially calculate the ratio of the intersection area to the area of the base station;
and the reservation module is configured to reserve the base stations with the ratio larger than a preset threshold value.
In some embodiments, the comparison module 903 includes:
a user module configured to determine users within the regional active base station based on a spatial index algorithm and user real-time location data;
and the real-time module is configured to compare the base station codes in the real-time position data of the users in the regional effective base station with the base station codes in the regional effective base station industrial parameters, keep the user with the same comparison result and obtain the number of real-time users in the regional effective base station.
The implementation process of the functions and roles of each module in the above device is specifically shown in the implementation process of the corresponding steps in the above method, and will not be described herein again.
Fig. 10 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure, and as shown in fig. 10, the embodiment of the present disclosure further provides an electronic device 1000 including at least one processor 1001 and a memory 1002 coupled to the processor 1001, where the memory 1002 is configured to store at least one processor 1001 executable instruction, and the at least one processor 1001 is configured to execute the instruction to implement the steps of the above-mentioned method in the embodiment of the present disclosure.
The processor 1001 may also be referred to as a central processing unit (Central Processing Unit, CPU), which may be an integrated circuit chip with signal processing capabilities. The steps in the above-described methods of the embodiments of the present disclosure may be accomplished by instructions in the form of integrated logic circuits or software in hardware in the processor 1001. The processor 1001 may be a general purpose processor, a digital signal processor (DIGITAL SIGNAL Processing, DSP), an ASIC, an off-the-shelf programmable gate array (Field-programmable GATE ARRAY, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method in connection with an embodiment of the present disclosure may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may reside in a memory 1002 such as random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The processor 1001 reads the information in the memory 1002 and in combination with its hardware performs the steps of the method described above.
Fig. 11 is a schematic structural diagram of an exemplary computer system provided in an embodiment of the present disclosure, and various operations/processes according to embodiments of the present disclosure may be implemented by software and/or firmware, and a program constituting the software may be installed from a storage medium or a network to a computer system having a dedicated hardware structure, for example, the computer system 1100 shown in fig. 11, which is capable of performing various functions including functions such as those described above, etc., when various programs are installed.
Computer system 1100 is intended to represent various forms of digital electronic computing devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 11, the computer system 1100 includes a computing unit 1101, and the computing unit 1101 can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 1102 or a computer program loaded from a storage unit 1108 into a Random Access Memory (RAM) 1103. In the RAM 1103, various programs and data required for the operation of the computer system 1100 can also be stored. The computing unit 1101, ROM 1102, and RAM 1103 are connected to each other by a bus 1104. An input output (I/O) interface 1105 is also connected to bus 1104.
Various components in computer system 1100 are connected to I/O interface 1105, including an input unit 1106, an output unit 1107, a storage unit 1108, and a communication unit 1109. The input unit 1106 may be any type of device capable of inputting information to the computer system 1100, and the input unit 1106 may receive input numeric or character information and generate key signal inputs related to user settings and/or function controls of the electronic device. The output unit 1107 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, video/audio output terminals, vibrators, and/or printers. Storage unit 1108 may include, but is not limited to, magnetic disks, optical disks. The communication unit 1109 allows the computer system 1100 to exchange information/data with other devices over a network, such as the internet, and may include, but is not limited to, modems, network cards, infrared communication device wireless communication transceivers and/or chipsets, e.g., bluetooth (TM) devices, WI-FI devices, wiMax devices, cellular communication devices, and/or the like.
The computing unit 1101 may be a variety of general purpose and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 1101 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 1101 performs the various methods and processes described above, e.g., in some embodiments, the above-described methods of the disclosed embodiments may be implemented as a computer software program tangibly embodied on a machine-readable medium, e.g., the storage unit 1108. In some embodiments, some or all of the computer programs may be loaded and/or installed onto the electronic device via ROM 1102 and/or communication unit 1109. In some embodiments, the computing unit 1101 may be configured to perform the above-described methods of embodiments of the present disclosure by any other suitable means (e.g., by means of firmware).
The present disclosure provides a computer-readable storage medium storing one or more programs executable by one or more processors to implement the above-described methods of the embodiments of the present disclosure.
The computer readable storage medium may be a volatile Memory (RAM) such as Random-Access Memory (RAM), or a non-volatile Memory (non-volatile Memory) such as Read-Only Memory (ROM), flash Memory (flash Memory), hard disk (HARD DISK DRIVE, HDD) or Solid state disk (Solid-state-STATE DRIVE, SSD), or may be a respective device including one or any combination of the above, such as a mobile phone, a computer, a tablet device, a personal digital assistant, etc.
It should be noted that the computer readable storage medium described above in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of a computer-readable storage medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to electrical wiring, fiber optic cable, RF (radio frequency), etc., or any suitable combination of the foregoing.
Embodiments of the present disclosure provide a computer program product comprising a computer program which, when executed by a processor, implements the steps of the demographic method described above.
In an embodiment of the present disclosure, computer program code for performing the operations of the present disclosure may be written in one or more programming languages, including but not limited to an object oriented programming language such as Java, smalltalk, C ++, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the computer, partly on the computer, as a stand-alone software package, partly on the computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The modules, components or units referred to in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of a module, component or unit does not in some cases constitute a limitation of the module, component or unit itself.
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary hardware logic components that may be used include Field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems-on-a-chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.
It should be noted that in this document, terms such as "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
The foregoing is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. 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 disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown and described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (13)
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