A mesh partitioning method, apparatus and electronic device

Abstract

The application discloses a mesh division method and device and electronic equipment, and relates to the technical field of communication, to solve the problem that the accuracy of the existing mesh division method is poor and it is difficult to meet the actual application requirements. The method comprises the following steps: obtaining a target geographical area, and dividing the target geographical area into N atomic meshes; obtaining signaling data of a target crowd in the target geographical area; determining target information according to the signaling data, wherein the target information comprises at least one of activity track information of the target crowd and population density information of the target geographical area; and performing merging processing on the N atomic meshes according to the target information, to obtain M target meshes, wherein each target mesh comprises a plurality of atomic meshes in the N atomic meshes. The embodiment of the application can ensure the accuracy of the target meshes obtained by division, so that the target meshes can better meet the requirements of actual application scenarios.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a grid partitioning method, apparatus and electronic device. Background Technology

[0002] With the technological development of internet electronic maps, visualization analysis, grid-based management and scheduling through electronic map grids have gradually become a mainstream digital management model. Therefore, it is particularly important to accurately divide the map grid according to actual application needs.

[0003] The methods for dividing map grids in related technologies mainly include grid division methods based on specified latitude and longitude ranges and placement intervals, and grid division methods based on point attributes and point features using specific algorithms. However, these methods generally suffer from poor grid division accuracy, making it difficult to meet the needs of practical applications. Summary of the Invention

[0004] This application provides a mesh generation method, apparatus, and electronic device to address the problem that existing mesh generation methods have poor accuracy and are difficult to meet practical application requirements.

[0005] In a first aspect, embodiments of this application provide a mesh generation method, including:

[0006] Obtain the target geographic region and divide the target geographic region into N atomic grids, where N is an integer greater than 1;

[0007] Obtain signaling data of the target population within the target geographical area;

[0008] Based on the signaling data, target information is determined, wherein the target information includes at least one of the activity trajectory information of the target population and the population density information of the target geographical area;

[0009] Based on the target information, the N atomic grids are merged to obtain M target grids, wherein each target grid includes several atomic grids from the N atomic grids, M is an integer greater than 1 and M is less than N.

[0010] Optionally, the target population includes grid management personnel, and the activity trajectory information of the target population includes the activity trajectory information of the grid management personnel within the target geographical area;

[0011] The step of merging the N atomic meshes according to the target information includes:

[0012] Based on the activity trajectory information, the geofence of the grid management personnel is determined;

[0013] Based on the atomic grids within the first geographic region corresponding to the geofence that intersect with the activity trajectory information, and the adjacent atomic grids within the first geographic region, the atomic grids within the first geographic region are merged to divide the first geographic region into at least one target grid.

[0014] Optionally, determining the geofence of the grid management personnel based on the activity trajectory information includes:

[0015] Based on the activity trajectory information and the road network data of the target geographic area, the geofence of the grid manager is generated using the minimum bounding polygon method, wherein the geofence is bounded by road lines.

[0016] Optionally, the step of merging the atomic grids within the first geographic region based on the atomic grids intersecting with the activity trajectory information within the first geographic region corresponding to the geofence, and the adjacent atomic grids within the first geographic region, includes:

[0017] Based on the atomic grids that intersect with the activity trajectory information within the first geographic area corresponding to the geofence, the adjacent atomic grids within the first geographic area, and the preset grid merging rules, the atomic grids within the first geographic area are merged.

[0018] The preset mesh merging rules include at least one of the following:

[0019] Maximize the intersection area, where the intersection area is the area where the merged grid intersects with the first geographic region;

[0020] Maximize the overlapping contour, which is the overlap between the contour of the merged grid and the contour of the geofence.

[0021] The area of ​​merged grids shall not exceed the preset maximum grid area;

[0022] The outline of the merged mesh meets the preset mesh boundary constraints.

[0023] Optionally, the step of merging the atomic grids within the first geographic region based on the atomic grids intersecting with the activity trajectory information within the first geographic region corresponding to the geofence, and the adjacent atomic grids within the first geographic region, to divide the first geographic region into at least one target grid, includes:

[0024] Based on the atomic grids that intersect with the activity trajectory information within the first geographic region corresponding to the geofence, and the adjacent atomic grids within the first geographic region, the atomic grids within the first geographic region are merged to obtain a first merged grid.

[0025] Calculate the matching degree between the first merged grid and the first geographic region;

[0026] If the matching degree meets the first preset condition, the first merged grid is determined to be the divided target grid.

[0027] Optionally, calculating the matching degree between the first merged grid and the first geographic region includes:

[0028] Based on the matching degree calculation formula: D=r×S+(1-r)×O, the matching degree between the first merged grid and the first geographic region is calculated, where r is the preset matching degree coefficient, D is the matching degree, S is the proportion of the intersection area of ​​the first geographic region and the first merged grid in the total area of ​​the first merged grid, and O is the proportion of the overlapping contour size of the first geographic region and the first merged grid in the contour size of the first merged grid.

[0029] Optionally, the target population includes ordinary active populations within the target geographical area, the target information includes population density information of the target geographical area, the population density information includes the number of permanent residents and the number of transient residents in the target geographical area, and includes the number of permanent residents and the number of transient residents in each of the N atomic grids;

[0030] The step of merging the N atomic meshes according to the target information includes:

[0031] The first population weight of the target geographical area is determined based on the number of permanent residents and the number of transient residents in the target geographical area.

[0032] Based on the number of permanent residents and the number of transient residents in each of the N atomic grids, the second population weight of each atomic grid is determined;

[0033] Based on the weights of the first and second population groups, the N atomic grids are merged.

[0034] Optionally, the weight of the first population group is the average population weight;

[0035] The merging process of the N atomic grids based on the first population weight and the second population weight includes:

[0036] Select the first atomic grid from the N atomic grids whose difference between the second population weight and the average population weight satisfies the second preset condition;

[0037] The first atomic grid and the second atomic grid are merged to obtain a second merged grid; wherein, the second atomic grid is the atomic grid that is adjacent to the first atomic grid among the N atomic grids;

[0038] Calculate the weights of the third population group in the second merged grid;

[0039] If the difference between the weight of the third population and the weight of the average population satisfies the third preset condition, the second merged grid is determined as the divided target grid.

[0040] Optionally, the population weight of the second geographic region is calculated according to the following formula:

[0041] Q = P + c × F, where Q is the population weight of the second geographical region, P is the number of permanent residents in the second geographical region, c is the floating population weight coefficient, and F is the number of floating residents in the second geographical region. The second geographical region is the target geographical region or the atomic grid.

[0042] Secondly, embodiments of this application also provide a mesh generation device, comprising:

[0043] The first processing module is used to acquire the target geographic region and divide the target geographic region into N atomic grids, where N is an integer greater than 1;

[0044] The acquisition module is used to acquire signaling data of the target population within the target geographical area;

[0045] The determination module is used to determine target information based on the signaling data, wherein the target information includes at least one of the activity trajectory information of the target population and the population density information of the target geographical area;

[0046] The second processing module is used to merge the N atomic grids according to the target information to obtain M target grids, wherein each target grid includes several atomic grids from the N atomic grids, M is an integer greater than 1 and M is less than N.

[0047] Optionally, the target population includes grid management personnel, and the activity trajectory information of the target population includes the activity trajectory information of the grid management personnel within the target geographical area;

[0048] The second processing module includes:

[0049] The first determining submodule is used to determine the geofence of the grid management personnel based on the activity trajectory information;

[0050] The first processing submodule is used to merge the atomic grids in the first geographical area based on the atomic grids that intersect with the activity trajectory information within the first geographical area corresponding to the geofence, as well as the adjacent atomic grids within the first geographical area, so as to divide the first geographical area into at least one target grid.

[0051] Optionally, the first determining submodule is used to generate a geofence for the grid manager based on the activity trajectory information and the road network data of the target geographic area using the minimum bounding polygon method, wherein the geofence is bounded by road lines.

[0052] Optionally, the first processing submodule is used to merge the atomic grids in the first geographical area based on the atomic grids that intersect with the activity trajectory information within the first geographical area corresponding to the geofence, the adjacent atomic grids within the first geographical area, and a preset grid merging rule.

[0053] The preset mesh merging rules include at least one of the following:

[0054] Maximize the intersection area, where the intersection area is the area where the merged grid intersects with the first geographic region;

[0055] Maximize the overlapping contour, which is the overlap between the contour of the merged grid and the contour of the geofence.

[0056] The area of ​​merged grids shall not exceed the preset maximum grid area;

[0057] The outline of the merged mesh meets the preset mesh boundary constraints.

[0058] Optionally, the first processing submodule includes:

[0059] The first merging unit is used to merge the atomic grids in the first geographical area based on the atomic grids that intersect with the activity trajectory information within the first geographical area corresponding to the geofence, and the adjacent atomic grids within the first geographical area, to obtain a first merged grid.

[0060] The first calculation unit is used to calculate the matching degree between the first merged grid and the first geographical region;

[0061] The first determining unit is used to determine the first merged grid as the divided target grid when the matching degree meets the first preset condition.

[0062] Optionally, the first calculation unit is used to calculate the matching degree between the first merged grid and the first geographic region based on the matching degree calculation formula: D=r×S+(1-r)×O, where r is a preset matching degree coefficient, D is the matching degree, S is the proportion of the intersection area of ​​the first geographic region and the first merged grid in the total area of ​​the first merged grid, and O is the proportion of the overlapping contour size of the first geographic region and the first merged grid in the contour size of the first merged grid.

[0063] Optionally, the target population includes ordinary active populations within the target geographical area, the target information includes population density information of the target geographical area, the population density information includes the number of permanent residents and the number of transient residents in the target geographical area, and includes the number of permanent residents and the number of transient residents in each of the N atomic grids;

[0064] The second processing module includes:

[0065] The first determining submodule is used to determine the first population weight of the target geographical area based on the number of permanent residents and the number of transient residents in the target geographical area.

[0066] The second determining submodule is used to determine the second population weight of each atomic grid based on the number of permanent residents and the number of transient residents in each of the N atomic grids;

[0067] The second processing submodule is used to merge the N atomic grids based on the first population weight and the second population weight.

[0068] Optionally, the weight of the first population group is the average population weight;

[0069] The second processing submodule includes:

[0070] The selection unit is used to select, from the N atomic grids, the first atomic grid whose difference between the second population weight and the average population weight satisfies the second preset condition;

[0071] The second merging unit is used to merge the first atomic grid and the second atomic grid to obtain a second merged grid; wherein, the second atomic grid is the atomic grid that is adjacent to the first atomic grid among the N atomic grids;

[0072] The second calculation unit is used to calculate the third population weight of the second merged grid;

[0073] The second determining unit is used to determine the second merged grid as the divided target grid when the difference between the third population weight and the average population weight meets the third preset condition.

[0074] Optionally, the population weight of the second geographic region is calculated according to the following formula:

[0075] Q = P + c × F, where Q is the population weight of the second geographical region, P is the number of permanent residents in the second geographical region, c is the floating population weight coefficient, and F is the number of floating residents in the second geographical region. The second geographical region is the target geographical region or the atomic grid.

[0076] Thirdly, embodiments of this application also provide an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps in the mesh partitioning method described above.

[0077] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in the meshing method described above.

[0078] In this embodiment, a target geographic region is acquired and divided into N atomic grids, where N is an integer greater than 1. Signaling data of the target population within the target geographic region is acquired. Based on the signaling data, target information is determined, including at least one of the activity trajectory information of the target population and the population density information of the target geographic region. Based on the target information, the N atomic grids are merged to obtain M target grids, where each target grid includes several atomic grids from the N atomic grids, and M is an integer greater than 1 and less than N. Thus, by dividing the target geographic region into several atomic grids of minimum grid units, and by combining the signaling data of the target population within the target geographic region to obtain the activity trajectory information of the target population and / or the population density information of the target geographic region, and then merging the atomic grids within the target geographic region based on the obtained information, it is possible to achieve grid division of the target geographic region that better fits the actual scenario based on the population activity trajectory and / or population distribution characteristics of the target geographic region. This ensures the accuracy of the obtained target grids and allows them to better meet the needs of actual application scenarios. Attached Figure Description

[0079] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0080] Figure 1 This is a flowchart of the mesh generation method provided in the embodiments of this application;

[0081] Figure 2 This is a structural diagram of the mesh generation device provided in the embodiments of this application;

[0082] Figure 3 This is a structural diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0083] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0084] See Figure 1 , Figure 1 This is a flowchart of the mesh generation method provided in the embodiments of this application, such as... Figure 1 As shown, it includes the following steps:

[0085] Step 101: Obtain the target geographic region and divide the target geographic region into N atomic grids, where N is an integer greater than 1.

[0086] The aforementioned target geographic area can refer to the geographic area that needs to be divided into map grids. For example, it can be the geographic location corresponding to an administrative region such as a province, city, district, county, or street. The specific target geographic area can be set by the user according to the needs of the actual application scenario.

[0087] In this embodiment of the application, the target geographic area can be first divided into several atomic grids of the smallest grid unit, and then these atomic grids can be merged separately according to certain rules to obtain the divided target grid.

[0088] Specifically, the target geographic area can be divided into atomic grids according to preset segmentation rules. For example, district / county or street surface data, along with road data at various levels (such as road data at levels 1-8), can be overlaid to generate atomic grids, so that each atomic grid corresponds to a district / county or a street. As another example, for a province / city, it can be divided into several atomic grids based on different regions and road data at various levels, with each atomic grid corresponding to a different region and including roads at different levels.

[0089] It should be noted that analysis of road data at all levels revealed that roads at level 8 and above already include roads within residential areas. Therefore, in practical applications, the road data at all levels for the target geographic area should be cleaned first to remove roads at level 8 and above. In the atomic mesh segmentation process, the logic of dividing surfaces into lines can be used to segment each district / county surface into multiple surface features based on roads. Furthermore, unclosed road lines can be removed, and the final retained surface features are generated into an atomic mesh that cannot be further subdivided.

[0090] Step 102: Obtain signaling data of the target population within the target geographical area.

[0091] Depending on the actual application scenario, the target population may specifically refer to the grid management personnel of the target geographical area, and may include one or more grid management personnel depending on the actual situation. If no grid management personnel are assigned in the target geographical area, the target population may include ordinary people active in the target geographical area.

[0092] In this step, in order to obtain the activity location data of the target population within the target geographical area, the signaling data of the target population within the target geographical area can be obtained, that is, the signaling data generated by the communication between the base station and the user terminal within the target geographical area can be obtained. Specifically, the relevant signaling data can be obtained from the operator. For example, for a grid manager, the corresponding signaling data can be obtained based on the terminal ID or mobile phone number used by the grid manager.

[0093] Step 103: Determine target information based on the signaling data, wherein the target information includes at least one of the activity trajectory information of the target population and the population density information of the target geographical area.

[0094] It should be noted that, in this embodiment of the application, after acquiring the signaling data, in order to ensure the accuracy of data processing and analysis, the signaling data can be preprocessed by denoising, filtering inaccurate data, etc. For example, mean filling, ping-pong effect and data drift data processing techniques can be used to preprocess the signaling data.

[0095] In this way, based on the preprocessed signaling data, the signaling data can be further analyzed and processed to obtain target information, such as determining the activity trajectory information of the target population and / or determining the population density information of the target geographical area through reasonable analysis and processing of the signaling data.

[0096] Specifically, based on the signaling data, the location information of the target population in the target geographical area at various time periods can be determined. Then, by connecting the locations of each point in chronological order, the activity trajectory information of the target population can be determined. Furthermore, by statistically analyzing the population density distribution of each area in the target geographical area at different time periods, the population density information of the target geographical area can be determined, such as the total population density information of the target geographical area, the population density information of each atomic grid in the target geographical area, etc.

[0097] In one implementation, a Deep Convolutional Generative Adversarial Network (DCGAN) can be used to train signaling data to determine virtual population density distribution information, such as generating a virtual population density distribution map using a DCGAN model. More specifically, call detail records (CDRs) and time and location feature data from user terminal signaling data can be obtained to plot estimated population density, resident population, and transient population data. This allows for further calculation of the population density distribution and quantity values ​​for each atomic grid, the population density distribution situation, the real-time status of the population at any location, the effect of changes in population flow over a period of time, travel trajectories, grid management personnel feature tags, resident population tags, and transient population tags, among other information.

[0098] Step 104: According to the target information, merge the N atomic grids to obtain M target grids, wherein each target grid includes several atomic grids from the N atomic grids, M is an integer greater than 1 and M is less than N.

[0099] In this step, the N atomic grids can be merged based on the target information, namely the activity trajectory information of the target population and / or the population density information of the target geographical area. For example, some of the N atomic grids that have a relationship can be merged into a large grid, thereby dividing the target geographical area into M target grids, each of which includes several atomic grids.

[0100] Specifically, in one embodiment, the atomic grids traversed by the target population in the target geographical area can be merged by referring to the activity trajectory information of the target population, so that the merged target grid matches the activity trajectory information of the target population. This helps to manage, schedule, inspect, visualize, and query information in the grid area corresponding to the activity range of the target population in practical applications. Moreover, this grid merging method is suitable for application scenarios that implement grid-based management of regions or populations.

[0101] In another implementation, atomic grids of the target geographic area can be merged based on population density distribution, referring to the population density information of the target geographic area. For example, atomic grids with similar population densities can be merged. Alternatively, several atomic grids can be merged based on the average population density of the target geographic area to ensure that the population density of the merged grid is close to the average population density of the target geographic area. Or, atomic grids with relatively consistent population label distributions in the target geographic area can be merged according to the population classification labels in the population density information. Other merging methods are also possible. This grid merging method is suitable for application scenarios that use grid-based management based on population density.

[0102] In another implementation, the two grid merging methods described above can be combined to merge atomic grids in the target geographic area to obtain a more diverse target grid that meets the needs of different application scenarios.

[0103] In addition, the grid merging method in this application embodiment has the advantage of being able to adjust the grid of the target geographical area based on the real-time signaling data of the target geographical area.

[0104] Optionally, the target population includes grid management personnel, and the activity trajectory information of the target population includes the activity trajectory information of the grid management personnel within the target geographical area;

[0105] Step 104 includes:

[0106] Based on the activity trajectory information, the geofence of the grid management personnel is determined;

[0107] Based on the atomic grids within the first geographic region corresponding to the geofence that intersect with the activity trajectory information, and the adjacent atomic grids within the first geographic region, the atomic grids within the first geographic region are merged to divide the first geographic region into at least one target grid.

[0108] In one embodiment, the target population may refer to grid management personnel. That is, in step 102, signaling data of grid management personnel in the target geographical area can be obtained. Specifically, the mobile phone signaling data of grid management personnel in the target geographical area during a specific time period (such as the time period of duty within the grid) can be obtained through preset grid management personnel feature tags (such as the user terminal ID or mobile phone number used by the grid management personnel in advance) or through grid management personnel feature tags obtained by statistical analysis.

[0109] In step 103, the activity trajectory information of the grid management personnel in the target geographical area can be determined based on the obtained mobile phone signaling data of the grid management personnel. Specifically, the base station locations passed by the grid management personnel can be obtained through the base station-related spatiotemporal data in the mobile phone signaling data and the base station positioning algorithm can be used to form a base station location sequence in chronological order. Finally, an approximate road segment trajectory sequence can be predicted through a hidden Markov chain model. This approximate road segment trajectory sequence can be used as the activity trajectory information of the grid management personnel.

[0110] The Hidden Markov Chain (HMM) model contains two sequences: a visible sequence (A1, A2, A3, ...) and a hidden sequence (B1, B2, B3, ...). In this HMM, the visible sequence (A1, A2, A3, ...) represents the sequence of base station locations traversed by the user, while the hidden sequence (B1, B2, B3, ...) represents the user's actual location sequence, which is also the user's predicted location sequence. The model works as follows: assuming the user is traveling on a road at a constant speed, the existing real road data within the base station coverage area is decomposed into road segments. These road segment sequences are used to represent the user's location sequence. Considering the base station coverage area, the model uses existing methods to calculate the matching probability between existing roads and base stations to obtain the matching probability between them. In this way, the signaling data of the grid management personnel can be used to predict their trajectory within each atomic grid in the target geographical area using the HMM.

[0111] In this implementation, a geofence representing the activity range of the grid management personnel can be determined based on the activity trajectory information. That is, the grid management personnel move within the geofence, and the activity trajectory of the grid management personnel must fall within the area represented by the geofence.

[0112] Optionally, determining the geofence of the grid management personnel based on the activity trajectory information includes:

[0113] Based on the activity trajectory information and the road network data of the target geographic area, the geofence of the grid manager is generated using the minimum bounding polygon method, wherein the geofence is bounded by road lines.

[0114] In one implementation, the geofence of the grid manager can be generated based on the activity trajectory information and the road network data of the target geographic area obtained in advance, as well as the road network topology of the target geographic area, using the minimum bounding polygon method. During the generation process, it can be ensured that the boundary of the geofence is the actual road line.

[0115] Then, based on the atomic grids that intersect with the activity trajectory information within the first geographical area corresponding to the geofence, and each adjacent atomic grid within the first geographical area, the atomic grids within the first geographical area can be merged separately, thereby dividing the first geographical area into several target grids.

[0116] Specifically, atomic grids that intersect with the activity trajectory of the grid manager within the first geographical area can be merged. Some adjacent grids can also be merged appropriately. To ensure the accuracy of the target grid obtained by merging, some grid merging conditions can be preset to limit the grid merging process. For example, the number of grids allowed to be merged, the maximum allowed area of ​​merged grids, and the outline boundary restrictions of merged grids can be set according to actual needs to ensure that the target grid obtained by merging meets expectations and is relatively accurate.

[0117] This implementation method ensures that the merged target grid matches the activity trajectory of the grid management personnel responsible for that grid area, thus ensuring that the divided target grid is more in line with the actual scenario and helps to manage the target geographical area in a grid-based manner in practical applications.

[0118] It should be noted that when there are multiple grid managers in the target geographic area, multiple geofences can be determined in the above manner. That is, one grid manager corresponds to one geofence, and one geofence corresponds to one geographic area. Thus, multiple geographic areas corresponding to multiple geofences can be merged into grids in the above manner, and each geographic area can be divided into one or more target grids.

[0119] In this way, the accuracy of the geofences generated by the grid management personnel can be guaranteed, and they are more in line with the actual scenario.

[0120] Optionally, the step of merging the atomic grids within the first geographic region based on the atomic grids intersecting with the activity trajectory information within the first geographic region corresponding to the geofence, and the adjacent atomic grids within the first geographic region, includes:

[0121] Based on the atomic grids that intersect with the activity trajectory information within the first geographic area corresponding to the geofence, the adjacent atomic grids within the first geographic area, and the preset grid merging rules, the atomic grids within the first geographic area are merged.

[0122] The preset mesh merging rules include at least one of the following:

[0123] Maximize the intersection area, where the intersection area is the area where the merged grid intersects with the first geographic region;

[0124] Maximize the overlapping contour, which is the overlap between the contour of the merged grid and the contour of the geofence.

[0125] The area of ​​merged grids shall not exceed the preset maximum grid area;

[0126] The outline of the merged mesh meets the preset mesh boundary constraints.

[0127] In one implementation, the atomic grids within the first geographic area can be merged using preset grid merging rules. These preset grid merging rules may include one or more of the following: maximizing the intersection area between the merged grid and the first geographic area, maximizing the overlap outline between the merged grid and the geographic fence, ensuring that the area of ​​the merged grid does not exceed a preset maximum grid area, ensuring that the outline of the merged grid meets preset grid boundary constraints, and ensuring that the number of target grids does not exceed a preset number. In other words, some grid merging conditions and rules can be preset to ensure that the target grid obtained after merging meets the actual requirements.

[0128] For example, you can pre-set the number of target grids to be divided, the maximum grid area, and whether the grid outline is allowed to cross district or street boundaries. You can also set the following grid merging rules:

[0129] a. Prioritize merging target atomic grids within the geofence area that intersect with the grid manager's trajectory;

[0130] b. Select and merge the atomic grids adjacent to the target atomic grid in turn;

[0131] The merging process in a and b above can be carried out in the following order from c to f.

[0132] c. The area of ​​the merged grid should intersect with the area of ​​the geofence as large as possible;

[0133] d. The outline of the merged grid should overlap with the outline of the geofence as closely as possible;

[0134] e. Based on the preset maximum grid area grid merging condition, determine whether the merged grid area does not exceed the preset maximum grid area;

[0135] f. Based on whether the preset mesh profile crosses the boundaries of districts or streets, the district / street boundaries are determined during the merging of atomic meshes. If the merged mesh has boundary restrictions of districts or streets, the atomic meshes that exceed the boundaries need to be removed from the merged mesh.

[0136] In this way, by merging the atomic grids in the first geographic area based on the above grid merging rules, it can be guaranteed that the final target grid that meets the actual needs and has high accuracy can be obtained.

[0137] Optionally, the step of merging the atomic grids within the first geographic region based on the atomic grids intersecting with the activity trajectory information within the first geographic region corresponding to the geofence, and the adjacent atomic grids within the first geographic region, to divide the first geographic region into at least one target grid, includes:

[0138] Based on the atomic grids that intersect with the activity trajectory information within the first geographic region corresponding to the geofence, and the adjacent atomic grids within the first geographic region, the atomic grids within the first geographic region are merged to obtain a first merged grid.

[0139] Calculate the matching degree between the first merged grid and the first geographic region;

[0140] If the matching degree meets the first preset condition, the first merged grid is determined to be the divided target grid.

[0141] In another embodiment, after each merging of atomic meshes within the first geographic region, the matching degree between the currently merged first merged mesh and the first geographic region can be calculated. Specifically, this can be calculated by combining the similarity between the two in terms of area, outline, etc., and it can be determined whether the currently calculated matching degree meets a first preset condition to determine whether the currently merged first merged mesh meets the requirements. The first preset condition can be the highest matching degree, the matching degree being greater than a preset value, etc. For example, the matching degree calculated after each mesh merging can be compared with the previous matching degree, and the merged mesh with the highest matching degree can be retained. After obtaining the highest matching degree, the current merging iteration process can be ended, and the merged mesh with the highest matching degree can be taken as the target mesh. The next round of atomic merging iteration can continue according to this principle until no more effective target meshes can be divided.

[0142] In this way, this implementation method can ensure that the target grid of the target geographical area has a high degree of overlap with the geofence of the grid management personnel in that area, which can also ensure that the target grid has high accuracy and is more in line with the needs of actual application scenarios.

[0143] Optionally, calculating the matching degree between the first merged grid and the first geographic region includes:

[0144] Based on the matching degree calculation formula: D=r×S+(1-r)×O, the matching degree between the first merged grid and the first geographic region is calculated, where r is the preset matching degree coefficient, D is the matching degree, S is the proportion of the intersection area of ​​the first geographic region and the first merged grid in the total area of ​​the first merged grid, and O is the proportion of the overlapping contour size of the first geographic region and the first merged grid in the contour size of the first merged grid.

[0145] In a more specific implementation, the matching degree calculation formula can be used: D = r × S + (1 - r) × O, to accurately calculate the matching degree between the first merged grid and the first geographic region, where r is the matching degree coefficient, S equals the intersection area of ​​the first geographic region and the first merged grid divided by the total area of ​​the first merged grid, and O equals the overlapping contour size of the first geographic region and the first merged grid divided by the contour size of the first merged grid. Furthermore, considering that the actual possibility of contour overlap is small in most cases, r = 0.8 can be taken, and the value of r can be dynamically adjusted according to the needs of the actual application scenario.

[0146] In this implementation, the matching degree calculation formula ensures the accuracy of the calculated matching degree and enables the division of target grids that are as close as possible to the geographical example areas of the grid management personnel.

[0147] Optionally, the target population includes ordinary active populations within the target geographical area, the target information includes population density information of the target geographical area, the population density information includes the number of permanent residents and the number of transient residents in the target geographical area, and includes the number of permanent residents and the number of transient residents in each of the N atomic grids;

[0148] Step 104 includes:

[0149] The first population weight of the target geographical area is determined based on the number of permanent residents and the number of transient residents in the target geographical area.

[0150] Based on the number of permanent residents and the number of transient residents in each of the N atomic grids, the second population weight of each atomic grid is determined;

[0151] Based on the weights of the first and second population groups, the N atomic grids are merged.

[0152] In another implementation, the target population can be ordinary active people within the target geographical area, and the atomic grids within the target geographical area can be merged and divided with reference to the population density information of the target geographical area. Specifically, in the case of geofenced areas within the target geographical area that do not currently have effective grid management personnel, the merging of atomic grids can be performed based on the signaling data of ordinary active people within the target geographical area.

[0153] In other words, in step 102, signaling data of the general population within the target geographical area can be obtained. In step 103, based on the obtained mobile phone signaling data of the general population within the target geographical area, the population density distribution information of the target geographical area can be determined, and then the population density information of the target geographical area can be analyzed. Specifically, this may include the number of permanent residents and the number of transient residents in the target geographical area, as well as the number of permanent residents and the number of transient residents in each of the N atomic grids of the target geographical area.

[0154] Furthermore, in this embodiment, the population weight of the target geographical area can be calculated based on the number of permanent residents and the number of transient residents, denoted as the first population weight. Specifically, a suitable population weight calculation method can be set according to actual needs. For example, different weights can be assigned to the permanent residents and the transient population respectively, and then a weighted sum can be calculated as the population weight by combining the population size and weights of both. The first population weight can be the total population weight, or it can be further calculated as the average population weight based on the desired number of target grids.

[0155] The population weight of each atomic grid can be calculated based on the number of permanent residents and the number of transient residents in each of the N atomic grids. This weight is denoted as the second population weight and can be calculated in a similar way to the population weight calculation method of the target geographical area.

[0156] Finally, the N atomic grids can be merged based on the first population weight and the second population weight. For example, the first population weight can be used as a benchmark to select several adjacent atomic grids among the N atomic grids for merging. The total population weight of the merged grid can be calculated so that the total population weight of the merged grid reaches a certain proportion of the first population weight, or is as close as possible to the first population weight (which is the average population weight), or the difference between the two weights is within an allowable range.

[0157] In this way, the target grid can be reasonably divided according to the regional population weight, which is conducive to grid-based management of the target geographical area based on the population distribution.

[0158] Optionally, the population weight of the second geographic region is calculated according to the following formula:

[0159] Q = P + c × F, where Q is the population weight of the second geographical region, P is the number of permanent residents in the second geographical region, c is the floating population weight coefficient, and F is the number of floating residents in the second geographical region. The second geographical region is the target geographical region or the atomic grid.

[0160] In one implementation, the population weight can be calculated using the population weight calculation formula: Q = P + c × F, where c is the floating population weight coefficient, P represents the number of permanent residents in a certain area, F is the number of floating residents in that area, and Q is the population weight of that area.

[0161] Specifically, the total population weight SUM of the target geographical area can be calculated as: the number of permanent residents in the target geographical area P + c × the number of migrants in the target geographical area F. The permanent residents and migrants can be calculated using the mobile signaling analysis method described above.

[0162] Similarly, the population weight sum for each atomic grid can be calculated as described above: resident population p + c × population flow f of that atomic grid.

[0163] In addition, considering that the actual cost of managing the floating population is usually greater than that of managing the permanent population, c>1 can be taken. c can be an empirical value. In some embodiments, c=1.2 can be taken, and the value of c can be flexibly set according to the actual application scenario.

[0164] Optionally, the weight of the first population group is the average population weight;

[0165] The merging process of the N atomic grids based on the first population weight and the second population weight includes:

[0166] Select the first atomic grid from the N atomic grids whose difference between the second population weight and the average population weight satisfies the second preset condition;

[0167] The first atomic grid and the second atomic grid are merged to obtain a second merged grid; wherein, the second atomic grid is the atomic grid that is adjacent to the first atomic grid among the N atomic grids;

[0168] Calculate the weights of the third population group in the second merged grid;

[0169] If the difference between the weight of the third population and the weight of the average population satisfies the third preset condition, the second merged grid is determined as the divided target grid.

[0170] In one specific implementation, the first population weight can be the average population weight. Specifically, the average population weight AVG of the target geographical area is SUM / pre-set number of target grids, where SUM is the total population weight of the target geographical area.

[0171] In this implementation, the atomic grids of the target geographic region can be merged according to the following rules:

[0172] 1) Select the first atomic grid from the N atomic grids whose difference between the second population weight and the average population weight satisfies the second preset condition. The second preset condition may be the smallest difference, the difference being within a certain range, etc. For example, an atomic grid whose population weight sum is closest to the average population weight AVG can be selected and denoted as the first atomic grid, and the subsequent merging iteration process can begin.

[0173] 2) Select the adjacent atomic grids (i.e., the second atomic grids) around the first atomic grid in sequence and merge them to obtain the second merged grid;

[0174] 3) Calculate the third population weight of the second merged grid. Specifically, during each merge, the population weight sum of each atomic grid merged this time is accumulated. During the iteration process, the aforementioned district or street boundary and grid area constraints can be met. Atomic grids with smaller sum and AVG differences are selected for merging.

[0175] 4) After continuously merging atomic meshes, when the cumulative sum and the difference between AVG meet the third preset condition, such as when the difference is the smallest, stop the current iteration and generate the target mesh;

[0176] 5) Continue the next iteration according to this principle until it is no longer possible to divide a valid target mesh.

[0177] It should be noted that after the above process is completed, if there are any other unmerged adjacent atomic meshes, they can be automatically merged into a new target mesh, and at this point all target meshes are divided.

[0178] In this way, the target geographic area can be divided into target grids according to the average distribution of population weights, thereby ensuring that the population distribution in each target grid is relatively consistent, which facilitates grid-based management of the target geographic area according to population weights.

[0179] As described above, this application provides a map gridding method based on mobile phone signaling. Using location data from historical mobile phone signaling of grid management personnel, the location trajectory is simulated using a Hidden Markov Chain algorithm and road network topology data to generate a geofence area for the grid management personnel. Atomic grids are generated by overlaying and segmenting district / county surface data and road line data at all levels. These atomic grids can only be merged, not split. The target grid is generated by progressively merging adjacent atomic grids. The merged grid is compared with the geofence area of ​​the grid management personnel, and the contours and intersection areas of the two areas are calculated to generate a matching degree. A higher contour overlap and a larger intersection area ratio result in a higher matching degree. After merging atomic grids, the target electronic map grid is automatically generated based on the area with the highest matching degree. Furthermore, to compensate for the lack of location trajectory data of grid management personnel in historical mobile phone signaling data, this application also proposes calculating the population distribution of the grid using signaling data and merging atomic grids using average population density weights to generate the target grid. In summary, the grid division method in this application combines data such as population distribution, road attributes, and dynamic trajectories of grid elements to solve problems such as poor grid division effect, large error, low efficiency, and weak practicality in grid management. The divided grid is closer to the actual production and life application scenarios and performs more efficiently in grid application management.

[0180] The embodiments of this application have the following technical advantages:

[0181] 1. By combining the location trajectory data of historical mobile phone signaling of grid management personnel within a specific time period with road data, a simulated grid is generated, resulting in high grid accuracy;

[0182] 2. The method of generating target map grids based on atomic grid merging and geofence area comparison combines the dynamic spatiotemporal data of the trajectory distribution of grid management personnel. The generated grids are more suitable for grid management and application scenarios targeting populations or regions, and the grids can be readjusted according to dynamic data.

[0183] 3. The method of dividing map grids based on the distribution weight of the grid population based on mobile phone signaling takes into account the label characteristics of the permanent population and the floating population. The divided grids are more suitable for the grid-based management of the population.

[0184] 4. The calculation method for the matching degree between the merged mesh and the simulated mesh considers two dimensions: intersection area and contour, which improves the success rate and accuracy of mesh matching. Furthermore, the comparison results can be further optimized by the variable parameter r to adapt to the mesh model.

[0185] 5. The method for generating grids based on operator-specific signaling data in this application provides a certain reference for grid-based management in the data economy, and can effectively ensure the security and compliance of users' privacy data.

[0186] This embodiment of the application acquires a target geographic region and divides the target geographic region into N atomic grids, where N is an integer greater than 1; acquires signaling data of the target population within the target geographic region; determines target information based on the signaling data, wherein the target information includes at least one of the activity trajectory information of the target population and the population density information of the target geographic region; and merges the N atomic grids based on the target information to obtain M target grids, wherein each target grid includes several atomic grids from the N atomic grids, where M is an integer greater than 1 and M is less than N. Thus, by dividing the target geographic region to be gridded into several atomic grids of the smallest grid unit, and by combining the signaling data of the target population within the target geographic region to obtain the activity trajectory information of the target population and / or the population density information of the target geographic region, and then merging the atomic grids within the target geographic region based on the obtained information, it is possible to achieve grid division of the target geographic region that better fits the actual scenario based on the population activity trajectory and / or population distribution characteristics of the target geographic region, ensuring the accuracy of the divided target grids and enabling them to better meet the needs of actual application scenarios.

[0187] This application also provides a mesh generation device. See [link to relevant documentation]. Figure 2 , Figure 2 This is a structural diagram of the mesh generation device provided in the embodiments of this application. Since the principle of the mesh generation device in solving the problem is similar to that of the mesh generation method in the embodiments of this application, the implementation of this mesh generation device can refer to the implementation of the method, and the repeated parts will not be described again.

[0188] like Figure 2 As shown, the mesh generation device 200 includes:

[0189] The first processing module 201 is used to acquire a target geographic region and divide the target geographic region into N atomic grids, where N is an integer greater than 1;

[0190] The acquisition module 202 is used to acquire signaling data of the target population within the target geographical area;

[0191] The determining module 203 is used to determine target information based on the signaling data, wherein the target information includes at least one of the activity trajectory information of the target population and the population density information of the target geographical area;

[0192] The second processing module 204 is used to merge the N atomic grids according to the target information to obtain M target grids, wherein each target grid includes several atomic grids from the N atomic grids, M is an integer greater than 1 and M is less than N.

[0193] Optionally, the target population includes grid management personnel, and the activity trajectory information of the target population includes the activity trajectory information of the grid management personnel within the target geographical area;

[0194] The second processing module 204 includes:

[0195] The first determining submodule is used to determine the geofence of the grid management personnel based on the activity trajectory information;

[0196] The first processing submodule is used to merge the atomic grids in the first geographical area based on the atomic grids that intersect with the activity trajectory information within the first geographical area corresponding to the geofence, as well as the adjacent atomic grids within the first geographical area, so as to divide the first geographical area into at least one target grid.

[0197] Optionally, the first determining submodule is used to generate a geofence for the grid manager based on the activity trajectory information and the road network data of the target geographic area using the minimum bounding polygon method, wherein the geofence is bounded by road lines.

[0198] Optionally, the first processing submodule is used to merge the atomic grids in the first geographical area based on the atomic grids that intersect with the activity trajectory information within the first geographical area corresponding to the geofence, the adjacent atomic grids within the first geographical area, and a preset grid merging rule.

[0199] The preset mesh merging rules include at least one of the following:

[0200] Maximize the intersection area, where the intersection area is the area where the merged grid intersects with the first geographic region;

[0201] Maximize the overlapping contour, which is the overlap between the contour of the merged grid and the contour of the geofence.

[0202] The area of ​​merged grids shall not exceed the preset maximum grid area;

[0203] The outline of the merged mesh meets the preset mesh boundary constraints.

[0204] Optionally, the first processing submodule includes:

[0205] The first merging unit is used to merge the atomic grids in the first geographical area based on the atomic grids that intersect with the activity trajectory information within the first geographical area corresponding to the geofence, and the adjacent atomic grids within the first geographical area, to obtain a first merged grid.

[0206] The first calculation unit is used to calculate the matching degree between the first merged grid and the first geographical region;

[0207] The first determining unit is used to determine the first merged grid as the divided target grid when the matching degree meets the first preset condition.

[0208] Optionally, the first calculation unit is used to calculate the matching degree between the first merged grid and the first geographic region based on the matching degree calculation formula: D=r×S+(1-r)×O, where r is a preset matching degree coefficient, D is the matching degree, S is the proportion of the intersection area of ​​the first geographic region and the first merged grid in the total area of ​​the first merged grid, and O is the proportion of the overlapping contour size of the first geographic region and the first merged grid in the contour size of the first merged grid.

[0209] Optionally, the target population includes ordinary active populations within the target geographical area, the target information includes population density information of the target geographical area, the population density information includes the number of permanent residents and the number of transient residents in the target geographical area, and includes the number of permanent residents and the number of transient residents in each of the N atomic grids;

[0210] The second processing module 204 includes:

[0211] The first determining submodule is used to determine the first population weight of the target geographical area based on the number of permanent residents and the number of transient residents in the target geographical area.

[0212] The second determining submodule is used to determine the second population weight of each atomic grid based on the number of permanent residents and the number of transient residents in each of the N atomic grids;

[0213] The second processing submodule is used to merge the N atomic grids based on the first population weight and the second population weight.

[0214] Optionally, the weight of the first population group is the average population weight;

[0215] The second processing submodule includes:

[0216] The selection unit is used to select, from the N atomic grids, the first atomic grid whose difference between the second population weight and the average population weight satisfies the second preset condition;

[0217] The second merging unit is used to merge the first atomic grid and the second atomic grid to obtain a second merged grid; wherein, the second atomic grid is the atomic grid that is adjacent to the first atomic grid among the N atomic grids;

[0218] The second calculation unit is used to calculate the third population weight of the second merged grid;

[0219] The second determining unit is used to determine the second merged grid as the divided target grid when the difference between the third population weight and the average population weight meets the third preset condition.

[0220] Optionally, the population weight of the second geographic region is calculated according to the following formula:

[0221] Q = P + c × F, where Q is the population weight of the second geographical region, P is the number of permanent residents in the second geographical region, c is the floating population weight coefficient, and F is the number of floating residents in the second geographical region. The second geographical region is the target geographical region or the atomic grid.

[0222] The mesh division device 200 provided in this application embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, so it will not be described again here.

[0223] The grid partitioning device 200 of this application embodiment acquires a target geographical region and divides the target geographical region into N atomic grids, where N is an integer greater than 1; acquires signaling data of a target population within the target geographical region; determines target information based on the signaling data, wherein the target information includes at least one of the activity trajectory information of the target population and the population density information of the target geographical region; and merges the N atomic grids based on the target information to obtain M target grids, wherein each target grid includes several atomic grids from the N atomic grids, where M is an integer greater than 1 and M is less than N. In this way, by dividing the target geographic area to be gridded into several atomic grids of the smallest grid units, and by combining the signaling data of the target population in the target geographic area, the activity trajectory information of the target population and / or the population density information of the target geographic area can be obtained. Then, based on the obtained information, the atomic grids in the target geographic area can be merged. This can achieve grid division of the target geographic area that is more in line with the actual scenario according to the population activity trajectory and / or population distribution characteristics, ensuring the accuracy of the divided target grid and enabling it to better meet the needs of actual application scenarios.

[0224] This application also provides an electronic device. Since the principle by which the electronic device solves the problem is similar to the mesh generation method in this application, the implementation of this electronic device can be found in the implementation of the method, and repeated details will not be described again. Figure 3 As shown, the electronic device according to an embodiment of this application includes:

[0225] Processor 300 is used to read the program from memory 320 and execute the following procedures:

[0226] Obtain the target geographic region and divide the target geographic region into N atomic grids, where N is an integer greater than 1;

[0227] Obtain signaling data of the target population within the target geographical area;

[0228] Based on the signaling data, target information is determined, wherein the target information includes at least one of the activity trajectory information of the target population and the population density information of the target geographical area;

[0229] Based on the target information, the N atomic grids are merged to obtain M target grids, wherein each target grid includes several atomic grids from the N atomic grids, M is an integer greater than 1 and M is less than N.

[0230] Among them, Figure 3In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 300) and memory (memory 320). The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. A bus interface provides the interface. Processor 300 is responsible for managing the bus architecture and general processing, and memory 320 can store data used by processor 300 during operation.

[0231] Optionally, the target population includes grid management personnel, and the activity trajectory information of the target population includes the activity trajectory information of the grid management personnel within the target geographical area;

[0232] Processor 300 is also used to read programs from memory 320 and perform the following steps:

[0233] Based on the activity trajectory information, the geofence of the grid management personnel is determined;

[0234] Based on the atomic grids within the first geographic region corresponding to the geofence that intersect with the activity trajectory information, and the adjacent atomic grids within the first geographic region, the atomic grids within the first geographic region are merged to divide the first geographic region into at least one target grid.

[0235] Optionally, the processor 300 is also used to read the program from the memory 320 and perform the following steps:

[0236] Based on the activity trajectory information and the road network data of the target geographic area, the geofence of the grid manager is generated using the minimum bounding polygon method, wherein the geofence is bounded by road lines.

[0237] Optionally, the processor 300 is also used to read the program from the memory 320 and perform the following steps:

[0238] Based on the atomic grids that intersect with the activity trajectory information within the first geographic area corresponding to the geofence, adjacent atomic grids within the first geographic area are merged according to a preset grid merging rule.

[0239] The preset mesh merging rules include at least one of the following:

[0240] Maximize the intersection area, where the intersection area is the area where the merged grid intersects with the first geographic region;

[0241] Maximize the overlapping contour, which is the overlap between the contour of the merged grid and the contour of the geofence.

[0242] The area of ​​merged grids shall not exceed the preset maximum grid area;

[0243] The outline of the merged mesh meets the preset mesh boundary constraints.

[0244] Optionally, the processor 300 is also used to read the program from the memory 320 and perform the following steps:

[0245] Based on the atomic grids that intersect with the activity trajectory information within the first geographic region corresponding to the geofence, and the adjacent atomic grids within the first geographic region, the atomic grids within the first geographic region are merged to obtain a first merged grid.

[0246] Calculate the matching degree between the first merged grid and the first geographic region;

[0247] If the matching degree meets the first preset condition, the first merged grid is determined to be the divided target grid.

[0248] Optionally, calculating the matching degree between the first merged grid and the first geographic region includes:

[0249] Based on the matching degree calculation formula: D=r×S+(1-r)×O, the matching degree between the first merged grid and the first geographic region is calculated, where r is the preset matching degree coefficient, D is the matching degree, S is the proportion of the intersection area of ​​the first geographic region and the first merged grid in the total area of ​​the first merged grid, and O is the proportion of the overlapping contour size of the first geographic region and the first merged grid in the contour size of the first merged grid.

[0250] Optionally, the target population includes ordinary active populations within the target geographical area, the target information includes population density information of the target geographical area, the population density information includes the number of permanent residents and the number of transient residents in the target geographical area, and includes the number of permanent residents and the number of transient residents in each of the N atomic grids;

[0251] Processor 300 is also used to read programs from memory 320 and perform the following steps:

[0252] The first population weight of the target geographical area is determined based on the number of permanent residents and the number of transient residents in the target geographical area.

[0253] Based on the number of permanent residents and the number of transient residents in each of the N atomic grids, the second population weight of each atomic grid is determined;

[0254] Based on the weights of the first and second population groups, the N atomic grids are merged.

[0255] Optionally, the weight of the first population group is the average population weight;

[0256] Processor 300 is also used to read programs from memory 320 and perform the following steps:

[0257] Select the first atomic grid from the N atomic grids whose difference between the second population weight and the average population weight satisfies the second preset condition;

[0258] The first atomic grid and the second atomic grid are merged to obtain a second merged grid; wherein, the second atomic grid is the atomic grid that is adjacent to the first atomic grid among the N atomic grids;

[0259] Calculate the weights of the third population group in the second merged grid;

[0260] If the difference between the weight of the third population and the weight of the average population satisfies the third preset condition, the second merged grid is determined as the divided target grid.

[0261] Optionally, the population weight of the second geographic region is calculated according to the following formula:

[0262] Q = P + c × F, where Q is the population weight of the second geographical region, P is the number of permanent residents in the second geographical region, c is the floating population weight coefficient, and F is the number of floating residents in the second geographical region. The second geographical region is the target geographical region or the atomic grid.

[0263] The electronic device provided in this application embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, so it will not be described again here.

[0264] Furthermore, the computer-readable storage medium of this application embodiment is used to store a computer program, which can be executed by a processor to implement as follows: Figure 1 Each step in the method embodiment shown.

[0265] In the several embodiments provided in this application, it should be understood that the disclosed methods and apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0266] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can be physically included separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0267] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute some steps of the transmission and reception methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0268] The above description is the preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principles described in this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A mesh generation method, characterized in that, include: Obtain the target geographic region and divide the target geographic region into N atomic grids, where N is an integer greater than 1; Obtain signaling data of the target population within the target geographical area; Based on the signaling data, target information is determined, wherein the target information includes at least one of the activity trajectory information of the target population and the population density information of the target geographical area; Based on the target information, the N atomic grids are merged to obtain M target grids, wherein each target grid includes several atomic grids from the N atomic grids, M is an integer greater than 1 and M is less than N; The target population includes ordinary active people within the target geographical area, and the target information includes population density information of the target geographical area, which includes the number of permanent residents and the number of transient residents in the target geographical area, as well as the number of permanent residents and the number of transient residents in each of the N atomic grids. The step of merging the N atomic meshes according to the target information includes: The first population weight of the target geographical area is determined based on the number of permanent residents and the number of transient residents in the target geographical area. Based on the number of permanent residents and the number of transient residents in each of the N atomic grids, the second population weight of each atomic grid is determined; Based on the weights of the first and second population groups, the N atomic grids are merged. The weight of the first population group is the average population weight; The merging process of the N atomic grids based on the first population weight and the second population weight includes: Select the first atomic grid from the N atomic grids whose difference between the second population weight and the average population weight satisfies the second preset condition; The first atomic grid and the second atomic grid are merged to obtain a second merged grid; wherein, the second atomic grid is the atomic grid that is adjacent to the first atomic grid among the N atomic grids; Calculate the weights of the third population group in the second merged grid; If the difference between the weight of the third population and the weight of the average population satisfies the third preset condition, the second merged grid is determined as the divided target grid.

2. The method according to claim 1, characterized in that, The target population also includes grid management personnel, and the activity trajectory information of the target population includes the activity trajectory information of the grid management personnel within the target geographical area; The step of merging the N atomic meshes according to the target information includes: Based on the activity trajectory information, the geofence of the grid management personnel is determined; Based on the atomic grids within the first geographic region corresponding to the geofence that intersect with the activity trajectory information, and the adjacent atomic grids within the first geographic region, the atomic grids within the first geographic region are merged to divide the first geographic region into at least one target grid.

3. The method according to claim 2, characterized in that, The step of determining the geofence of the grid management personnel based on the activity trajectory information includes: Based on the activity trajectory information and the road network data of the target geographic area, the geofence of the grid manager is generated using the minimum bounding polygon method, wherein the geofence is bounded by road lines.

4. The method according to claim 2, characterized in that, The merging process of atomic grids within the first geographic region, based on the atomic grids intersecting with the activity trajectory information within the first geographic region corresponding to the geofence, and the adjacent atomic grids within the first geographic region, includes: Based on the atomic grids intersecting with the activity trajectory information within the first geographic area corresponding to the geofence, the adjacent atomic grids within the first geographic area, and the preset grid merging rules, the atomic grids within the first geographic area are merged. The preset mesh merging rules include at least one of the following: Maximize the intersection area, where the intersection area is the area where the merged grid intersects with the first geographic region; Maximize the overlapping contour, which is the overlap between the contour of the merged grid and the contour of the geofence. The area of ​​merged grids shall not exceed the preset maximum grid area; The outline of the merged mesh meets the preset mesh boundary constraints.

5. The method according to claim 2, characterized in that, The process of merging atomic grids within the first geographic region corresponding to the geofence that intersect with the activity trajectory information, and adjacent atomic grids within the first geographic region, to divide the first geographic region into at least one target grid, includes: Based on the atomic grids that intersect with the activity trajectory information within the first geographic region corresponding to the geofence, and the adjacent atomic grids within the first geographic region, the atomic grids within the first geographic region are merged to obtain a first merged grid. Calculate the matching degree between the first merged grid and the first geographic region; If the matching degree meets the first preset condition, the first merged grid is determined to be the divided target grid.

6. The method according to claim 5, characterized in that, The calculation of the matching degree between the first merged grid and the first geographic region includes: Based on the matching degree calculation formula: D=r×S+(1-r)×O, the matching degree between the first merged grid and the first geographic region is calculated, where r is the preset matching degree coefficient, D is the matching degree, S is the proportion of the intersection area of ​​the first geographic region and the first merged grid in the total area of ​​the first merged grid, and O is the proportion of the overlapping contour size of the first geographic region and the first merged grid in the contour size of the first merged grid.

7. The method according to claim 1, characterized in that, The population weight of the second geographic region is calculated according to the following formula: Q = P + c × F, where Q is the population weight of the second geographical region, P is the number of permanent residents in the second geographical region, c is the floating population weight coefficient, and F is the number of floating residents in the second geographical region. The second geographical region is the target geographical region or the atomic grid.

8. A grid dividing device, characterized in that, include: The first processing module is used to acquire the target geographic region and divide the target geographic region into N atomic grids, where N is an integer greater than 1; The acquisition module is used to acquire signaling data of the target population within the target geographical area; The determination module is used to determine target information based on the signaling data, wherein the target information includes at least one of the activity trajectory information of the target population and the population density information of the target geographical area; The second processing module is used to merge the N atomic grids according to the target information to obtain M target grids, wherein each target grid includes several atomic grids from the N atomic grids, M is an integer greater than 1 and M is less than N; The target population includes ordinary active people within the target geographical area, and the target information includes population density information of the target geographical area, which includes the number of permanent residents and the number of transient residents in the target geographical area, as well as the number of permanent residents and the number of transient residents in each of the N atomic grids. The second processing module includes: The first determining submodule is used to determine the first population weight of the target geographical area based on the number of permanent residents and the number of transient residents in the target geographical area. The second determining submodule is used to determine the second population weight of each atomic grid based on the number of permanent residents and the number of transient residents in each of the N atomic grids; The second processing submodule is used to merge the N atomic grids based on the first population weight and the second population weight; The weight of the first population group is the average population weight; The second processing submodule includes: The selection unit is used to select, from the N atomic grids, the first atomic grid whose difference between the second population weight and the average population weight satisfies the second preset condition; The second merging unit is used to merge the first atomic grid and the second atomic grid to obtain a second merged grid; wherein, the second atomic grid is the atomic grid that is adjacent to the first atomic grid among the N atomic grids; The second calculation unit is used to calculate the third population weight of the second merged grid; The second determining unit is used to determine the second merged grid as the divided target grid when the difference between the third population weight and the average population weight meets the third preset condition.

9. An electronic device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor; characterized in that the processor is configured to read the program from the memory to implement the steps in the meshing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium for storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps in the mesh generation method as described in any one of claims 1 to 7.

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