CN112836991A - Site planning method and device, terminal equipment and readable storage medium - Google Patents
Site planning method and device, terminal equipment and readable storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a site planning method, a site planning device, terminal equipment and a readable storage medium, wherein each target grid in an area to be planned is obtained according to a preset site planning theme; initially converging each target grid by using a preset initial convergence parameter to filter discrete grids in each target grid and determine a plurality of connected sub-areas; splitting and converging the grids in each continuous sub-area by using a preset splitting and converging parameter to split each continuous sub-area and determine a plurality of independent sub-areas; combining the independent sub-regions by using a preset combination convergence parameter to determine a plurality of combined sub-regions, wherein the combined sub-region is composed of one or more independent sub-regions; filtering each merging subarea by using a preset zooming convergence parameter to determine convergence windows and output grids in each convergence window; and planning the site position in the area to be planned according to each convergence window and each output grid. And reasonable setting of the position of the base station is realized.
Description
Technical Field
The present invention relates to the field of data analysis, and in particular, to a method and an apparatus for site planning, a terminal device, and a readable storage medium.
Background
At present, the conventional 4/5G network site planning scheme in the communication industry is mainly completed through manual analysis, and a planner analyzes network coverage data of an operator by using a notebook computer and combining data analysis software, manually plans a 4/5G network site, and adds information such as site names, site positions, site longitude and latitude and the like to the planned site.
Based on the network coverage condition of the manual analysis operator, site planning is carried out on the analyzed weak coverage area, and the whole planning process has the following defects: the number of workers to be invested is large: according to statistics, 3-5 workers are needed for completing network planning of 1 city; the work efficiency is low: according to statistics, 10-15 working days are needed for completing the network planning of 1 city; the resource investment is large: besides the labor cost, resources such as a notebook computer and analysis software need to be equipped for each worker.
Disclosure of Invention
In view of the foregoing problems, the present application provides a method, an apparatus, a terminal device and a readable storage medium for site planning.
The application provides a site planning method, which comprises the following steps:
acquiring each target grid in an area to be planned according to a preset site planning theme;
initially converging each target grid by using a preset initial convergence parameter to filter discrete grids in each target grid and determine a plurality of connected sub-areas;
splitting and converging the grids in each continuous sub-area by using a preset splitting and converging parameter to split each continuous sub-area and determine a plurality of independent sub-areas;
merging the independent sub-regions by using a preset merging convergence parameter to determine a plurality of merged sub-regions, wherein the merged sub-regions are formed by one or more independent sub-regions;
filtering each merging subarea by using a preset zooming convergence parameter to determine convergence windows and output grids in each convergence window;
and planning the site positions in the area to be planned according to the convergence windows and the output grids.
The site planning method according to the present application, where the initial convergence parameter includes a convergence radius and a threshold value of the number of target grids in each convergence region, and the initial convergence is performed on each target grid by using a predetermined initial convergence parameter to filter discrete grids in each target grid and determine a plurality of connected sub-regions, includes:
drawing circles based on the convergence radius by taking each target grid as a circle center, and determining the number of the target grids in each circle, wherein the circle center is any point in the target grids;
judging whether the number of the target grids in each circle is larger than or equal to the number threshold value;
if the number is smaller than the number threshold value, filtering and deleting the target grids and the corresponding circular boundaries in the corresponding circles;
and determining a plurality of connected sub-areas in the area to be planned according to the remaining target grids in the circle which is larger than or equal to the number threshold value.
The station planning method according to the present application, the splitting and converging parameter includes a maximum distance threshold value and a number threshold added value, and the splitting and converging of the grid in each continuous sub-region by using the predetermined splitting and converging parameter to split and converge the grid in each continuous sub-region to split each continuous sub-region and determine a plurality of independent sub-regions includes:
taking the average value of the longitudes and the average value of the latitudes of the center points of each grid in the connected sub-areas as the connected center points of the corresponding connected sub-areas;
determining the maximum connected slice distance from each grid central point in the connected slice subarea to the connected slice central point;
if the maximum link distance is larger than the maximum distance threshold value, updating the number threshold value by using a number threshold increasing value;
re-converging the grids in each continuous sub-area by using the updated number threshold value and the convergence radius and determining a discrete grid until the maximum continuous distance of each continuous sub-area is smaller than or equal to the maximum distance threshold value, wherein each continuous sub-area is used as an independent sub-area;
and sequentially adding qualified discrete grids to the adjacent independent sub-areas according to a preset discrete grid adding condition.
The station planning method according to the present application, where the merging aggregation parameter includes a merging threshold ratio, and the merging each independent sub-region by using the predetermined merging aggregation parameter to determine a plurality of merged sub-regions includes:
determining the longitude average value of each grid center point in the independent subareas to be merged and the center point of the area to be merged corresponding to the latitude average value;
determining the maximum independent distance from each grid central point in the independent sub-areas to be merged to the central point of the area to be merged;
respectively determining the central points of the independent sub-areas to be combined;
determining the grid center point distance between each grid center point in the independent sub-areas to be combined and the center point of the corresponding independent sub-area;
determining the average grid center point distance of each independent sub-area to be combined according to each grid center point distance;
determining a first ratio of the distance between the center points of the independent sub-areas to be combined to the sum of the distances of the center points of the average grids;
and if the maximum independent distance is smaller than or equal to the maximum distance threshold value and the first ratio is smaller than the combination threshold ratio, combining the independent sub-regions to be combined.
The site planning method according to the present application, where the scaling aggregation parameter includes a discrete distance ratio threshold and a window density threshold, and the filtering is performed on each merged sub-region by using a predetermined scaling aggregation parameter to determine an aggregation window and an output grid in each aggregation window, includes:
taking the average value of the longitude and the average value of the latitude of each grid central point in each merging subarea as the merging central point of the corresponding merging subarea;
determining the maximum merging distance and the average merging distance from each grid central point in the merging subarea to the merging central point;
determining a second ratio between the maximum combining distance and the average combining distance;
if the second ratio is larger than the discrete distance ratio threshold value, taking each grid in the corresponding merged sub-area as a discrete grid, and deleting the boundary of the corresponding merged sub-area;
sequentially adding the qualified discrete grids to the adjacent merging sub-regions according to a preset discrete grid adding condition;
the rest merging subregions are used as the convergence windows;
and taking the rest grids in the rest merging subareas as the output grids.
In the site planning method of the present application, the discrete grid adding condition includes: the distance between the discrete grid and the central point of the region to be added is smaller than a preset distance threshold value; after the discrete grids are added to the area to be added, the new density value of the area to be added is greater than or equal to the original density value; the maximum distance value of the region to be added after the discrete grid is added is smaller than or equal to the maximum distance threshold value; the region to be added is a combined sub-region or an independent sub-region.
The calculating step of the density of the region to be added comprises the following steps:
determining the number of grids, of which the distance from each grid in the region to be added to the central point of the region to be added is smaller than the average distance of the region to be added;
the density of the region to be added is calculated using the following formula:
ρ＝num*s1s, p represents the density of the region to be added, S1And representing a predetermined grid area, S representing a divergence area corresponding to the region to be added, and d ═ d ×. pi, d representing an average distance of the region to be added.
The site planning method according to the present application, planning the site position in the to-be-planned area according to each convergence window and each output grid, includes:
determining the boundary of the ith convergence window;
drawing a jth ray corresponding to an mth starting point based on the direction from the mth starting point at the ith convergence window boundary to the center point of the jth convergence window by taking an output grid at the ith convergence window boundary as the starting point, wherein i is not equal to j, i is not more than N, j is not more than N, and N is the total number of the convergence windows;
if the boundary of the jth ray corresponding to the mth starting point and the jth convergence window has odd intersection points, deleting the mth starting point;
re-determining the boundary of the ith convergence window until the ray corresponding to each boundary point in the ith convergence window has even intersection points with the boundaries of other convergence windows;
and determining the site position in the area to be planned according to the remaining output grids in each convergence window.
The application provides a station planning device, the device includes:
the acquisition module is used for acquiring each target grid in the area to be planned according to a preset site planning theme;
the convergence module is used for initially converging each target grid by using a preset initial convergence parameter so as to filter discrete grids in each target grid and determine a plurality of connected sub-areas;
the splitting module is used for splitting and converging the grids in each continuous sub-area by using a preset splitting and converging parameter so as to split each continuous sub-area and determine a plurality of independent sub-areas;
the merging module is used for merging each independent sub-region by utilizing a preset merging convergence parameter to determine a plurality of merged sub-regions, and each merged sub-region consists of one or more independent sub-regions;
the zooming module is used for filtering each merging subarea by using a preset zooming convergence parameter so as to determine convergence windows and output grids in each convergence window;
and the planning module is used for planning the site positions in the area to be planned according to the convergence windows and the output grids.
The application provides a terminal device, which comprises a memory and a processor, wherein the memory stores a computer program, and the computer program executes the site planning method when running on the processor.
The present application proposes a readable storage medium storing a computer program which, when run on a processor, performs the site planning method described herein.
According to the site planning method, the site positions in the area to be planned are planned by utilizing the clustered convergence windows and the output grids in the convergence windows through initial convergence, splitting convergence, merging convergence and zooming convergence. The initial convergence can filter part of discrete grids, reduce the regions where the grids are sparse step by step, reduce the complexity of the subsequent convergence process and improve the operation efficiency of the system; after initial convergence, each grid of the map can generate a large-area continuous sub-area which exceeds the coverage radius of the base station, so that the large-area continuous sub-area which does not conform to the actual coverage scene of the base station needs to be split, and when the base station is positioned at the center of each independent sub-area, each corner of each independent sub-area is ensured to be in the coverage range of the base station through splitting and convergence; after splitting and converging, a plurality of smaller independent sub-areas are formed, and in order to ensure effective utilization and full utilization of base station equipment, each base station needs to cover some areas as much as possible, so that the independent sub-areas screened after splitting and converging need to be merged and converged. After merging convergence, there may also be some merged sub-regions with sparser grids, or there may be some off-grids in the merged sub-regions. Therefore, the correction and screening are performed for some deviated grids existing in the merged sub-region and the merged sub-region with sparser grids. And finally, automatically generating the boundaries of the clustered convergence windows to form a closed area, and ensuring that the boundaries of the clustered convergence windows do not have an overlapping condition. The technical scheme of this application effectively reduces the cost of labor to improve work efficiency.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings required to be used in the embodiments will be briefly described below, and it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope of the present invention. Like components are numbered similarly in the various figures.
Fig. 1 is a schematic flowchart illustrating a site planning method according to an embodiment of the present application;
fig. 2 is a schematic diagram of a grid map according to an embodiment of the present application;
FIG. 3 illustrates another grid map schematic proposed by an embodiment of the present application;
fig. 4 is a schematic flowchart illustrating initial aggregation in a site planning method according to an embodiment of the present application;
fig. 5 is a schematic diagram illustrating an initial aggregation process in a site planning method according to an embodiment of the present application;
FIG. 6 is a schematic diagram of 2 connected subregions according to an embodiment of the present application;
fig. 7 is a schematic flow chart illustrating splitting and converging in a site planning method according to an embodiment of the present application;
FIG. 8 is a schematic diagram of a sub-area of a wafer according to an embodiment of the present application;
fig. 9 is a schematic diagram illustrating a split and aggregation process of contiguous sub-regions according to an embodiment of the present application;
fig. 10 is a schematic flow chart illustrating merging and converging in a site planning method according to an embodiment of the present application;
fig. 11 is a schematic diagram illustrating two independent sub-regions to be merged according to an embodiment of the present application;
fig. 12 is a schematic flowchart illustrating scaling and aggregation in a site planning method according to an embodiment of the present application;
fig. 13 is a schematic diagram illustrating a merged sub-region proposed in the embodiment of the present application;
FIG. 14 is a flow chart illustrating a process for determining a boundary of a convergence window according to an embodiment of the present application;
FIG. 15 is a schematic diagram of a grid map after determining a boundary of a convergence window according to an embodiment of the present application;
fig. 16 shows a schematic structural diagram of a station planning apparatus according to an embodiment of the present application.
Description of the main element symbols:
10-a station planning device; 11-an acquisition module; 12-a convergence module; 13-splitting the module; 14-a merging module; 15-a scaling module; 16-planning module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Hereinafter, the terms "including", "having", and their derivatives, which may be used in various embodiments of the present invention, are only intended to indicate specific features, numbers, steps, operations, elements, components, or combinations of the foregoing, and should not be construed as first excluding the existence of, or adding to, one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
Furthermore, the terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the present invention belong. The terms (such as those defined in commonly used dictionaries) should be interpreted as having a meaning that is consistent with their contextual meaning in the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in various embodiments of the present invention.
The method comprises the steps of clustering each grid of a map coded by GeoHash based on a brand-new clustering algorithm, wherein the clustering process comprises initial convergence, splitting convergence, merging convergence and zooming convergence, and planning the site positions in the to-be-planned area by using each converged window after clustering and each output grid in each converged window.
The initial convergence can filter part of discrete grids, reduce the regions where the grids are sparse step by step, reduce the complexity of the subsequent convergence process and improve the operation efficiency of the system; after initial convergence, each grid of the map can generate a large-area continuous sub-area which exceeds the coverage radius of the base station, so that the large-area continuous sub-area which does not conform to the actual coverage scene of the base station needs to be split, and when the base station is positioned at the center of each independent sub-area, each corner of each independent sub-area is ensured to be in the coverage range of the base station through splitting and convergence; after splitting and converging, a plurality of smaller independent sub-areas are formed, and in order to ensure effective utilization and full utilization of base station equipment, each base station needs to cover some areas as much as possible, so that the independent sub-areas screened after splitting and converging need to be merged and converged. After merging convergence, there may also be some merged sub-regions with sparser grids, or there may be some off-grids in the merged sub-regions. Therefore, the correction and screening are performed for some deviated grids existing in the merged sub-region and the merged sub-region with sparser grids.
And finally, automatically generating the boundaries of the clustered convergence windows to form a closed area, and ensuring that the boundaries of the clustered convergence windows do not have an overlapping condition.
Example 1
In one embodiment of the present application, referring to fig. 1, a site planning method is shown that includes the following steps:
s100: and obtaining each target grid in the area to be planned according to a preset site planning topic.
It can be understood that the area to be planned is a site planning oriented to a communication industry operator network, and a reasonable base station position needs to be planned in the area to be planned, so that the minimum base stations are ensured to be arranged in the area to be planned, and each base station is ensured to cover some areas as much as possible.
The area to be planned may be presented in the form of a grid map. For example, different topical data may be output according to a predetermined site planning topic based on rasterized data in an "internet OTT big data analysis platform". For example: the "RSRP mean coverage topic" of the 2/3/4/5G network of each communication carrier may be output according to the "RSRP (Reference Signal Receiving Power) mean value" in the grid attribute; the special problem of the density of the sampling points can be output according to the quantity of the sampling points in the grid attribute; the special problem of weak coverage proportion can be output according to the proportion of the RSRP < -105dbm sampling points in the grid attribute to the total sampling points; meanwhile, the system also comprises a value area topic, a convergence service topic, a network competition pair topic, a broadband topic, a terminal topic and the like. It can be understood that the user can obtain each target grid corresponding to the predetermined site planning topic in the area to be planned according to the predetermined site planning topic. The grid size is 19 meters by 38 meters and 25 meters by 25 meters, and can be selected according to requirements.
Exemplarily, referring to fig. 2, a grid map is shown, wherein each grid has a size of 19 meters by 38 meters, and each grid is labeled with a different color according to the RSRP average value, and the color of the grid is gradually deepened as the RSRP average value corresponding to the grid is decreased. It is understood that RSRP is one of the key parameters and physical layer measurement requirements in an LTE network that can represent the radio signal strength, and is the average of the received signal power over all resource elements that carry reference signals within a certain symbol. The smaller the RSRP average value, the worse the base station signal coverage.
Exemplarily, the present embodiment obtains each target grid in the region to be planned according to a predetermined RSRP mean value coverage topic, that is, a grid in the region to be planned, whose RSRP mean value is < -105dbm, is used as a target grid for subsequent analysis processing. Exemplarily, after obtaining each target grid with RSRP average value < -105dbm in the area to be planned, a grid map corresponding to the area to be planned is shown in fig. 3.
S200: and initially converging each target grid by using a preset initial convergence parameter to filter discrete grids in each target grid and determine a plurality of connected sub-areas.
The initial convergence parameters include a convergence radius and a threshold number of target grids in each convergence region. Each convergence area is circular, and the corresponding radius is a preset convergence radius. The purpose of initial convergence is to delete discrete grids, so the convergence radius can be 50 m-200 m, the specific configuration can be set according to the size of the grids, and the larger the area of the grids is, the larger the set convergence radius is.
If the number of the target grids in each convergence region is smaller than a preset number threshold value, the grids in the convergence region are discrete grids and can be deleted.
It can be understood that part of discrete grids can be filtered through initial convergence, the region where the grids are sparse step by step is reduced, the complexity of the subsequent convergence process is reduced, and the system operation efficiency is improved.
S300: and splitting and converging the grids in each continuous sub-area by using a preset splitting and converging parameter to split each continuous sub-area and determine a plurality of independent sub-areas.
After the initial convergence, each grid of the map generates a large-area continuous sub-area, and the large-area continuous sub-area exceeds the coverage radius of the base station, so that the grids in each continuous sub-area are split and converged by using a preset splitting and converging parameter to split each continuous sub-area and determine a plurality of independent sub-areas. And the splitting and gathering ensure that each corner of each independent sub-area is within the coverage range of the base station when the base station is positioned in the center of each independent sub-area.
S400: and combining the independent sub-areas by utilizing a preset combination convergence parameter to determine a plurality of combined sub-areas, wherein the combined sub-areas are formed by one or more independent sub-areas.
After splitting and converging, a plurality of smaller independent sub-areas are formed, and in order to ensure effective utilization and full utilization of base station equipment, each base station needs to cover some areas as much as possible, so that each independent sub-area needs to be merged by using a predetermined merging and converging parameter to determine a plurality of merged sub-areas, wherein each merged sub-area is composed of one or more independent sub-areas.
S500: and filtering each merging subarea by using a preset scaling convergence parameter to determine convergence windows and output grids in each convergence window.
After merging convergence, there may also be some merged sub-regions with sparser grids, or there may be some off-grids in the merged sub-regions. Therefore, each merging sub-region needs to be filtered by using a predetermined scaling convergence parameter to determine a convergence window and an output grid in each convergence window. And correcting and screening the combined subareas with sparse grids against some deviated grids in the combined subareas.
S600: and planning the site positions in the area to be planned according to the convergence windows and the output grids.
And automatically generating the boundaries of the clustered convergence windows according to the convergence windows and the output grids to form a closed area, and ensuring that the boundaries of the clustered convergence windows do not overlap. And planning the site positions in the area to be planned based on each closed area.
Example 2
One embodiment of the present application, referring to fig. 4, illustrates that initial convergence comprises the following steps:
s210: and drawing circles based on the convergence radius by taking each target grid as a circle center, and determining the number of the target grids in each circle, wherein the circle center is any point in the target grids.
The convergence radius may be preset according to the area of the grid, for example, if the area of the grid is 19 m × 38 m, the convergence radius may be preset to 100. And drawing a circle based on the convergence radius by taking each target grid as a circle center, and determining the number of the target grids in each circle. It will be appreciated that at a convergence radius of 100, the corresponding circular convergence region comprises a maximum of 43 grids 19 m x 38 m in area, and a minimum of 1 grid 19 m x 38 m in area, i.e. the grid at the center of the circular convergence region. The number of target grids in each circle can be determined according to the actual situation of the area to be planned.
The circle center is any point in the target grid, preferably, the circle center is the center of the target grid, namely the intersection point of the diagonals of the target grid. It can be understood that if the center of the target grid is taken as the center of a circle, the accuracy of initial convergence can be ensured, part of discrete grids can be effectively filtered, the areas with sparse grids in steps are reduced, the complexity of the subsequent convergence process is reduced, and the system operation efficiency is improved.
S220: and judging whether the number of the target grids in each circle is larger than or equal to the number threshold value.
The number threshold value can be set in advance according to user requirements and can be set according to the size of the target grid and the size of the convergence radius. Exemplarily, the number threshold may be set to 4 when the convergence radius is 100m and the size of the target grid is 19 m × 38 m.
Further, it is determined whether the number of target grids in each circle is greater than the number threshold, and if the number is less than the number threshold, step S230 is executed. If the number is greater than or equal to the number threshold, step S231 is executed.
S230: the filtering deletes the target grid and the corresponding circle boundary in the corresponding circle.
S231: the target grid and the corresponding circular boundary in the corresponding circle are retained.
S240: and determining a plurality of connected sub-areas in the area to be planned according to the remaining target grids in the circle which is larger than or equal to the number threshold value.
Exemplarily, referring to fig. 5, in the figure, the number of the target grids in the circle of the solid line boundary is greater than or equal to the preset number threshold, the target grids in the circle of the solid line boundary and the circle of the solid line boundary are retained, the number of the target grids in the circle of the dotted line boundary is smaller than the preset number threshold, the target grids in the circle of the dotted line boundary and the circle of the dotted line boundary are deleted, and finally, 2 connected sub-regions as shown in fig. 6 are obtained. It should be understood that the number of target grids in the area to be planned is much larger than the number of grids shown in fig. 5, which fig. 5 is only schematically illustrated.
Further, when traversing each target grid, that is, drawing a circle with each target grid as a circle center, a point may be randomly selected to make a circle, and then it is determined whether the number of target grids in the circle is smaller than a preset number threshold, if so, the target grids in the circle and the circle are directly deleted, and then the next target grid is traversed until all target grids are traversed. It can be understood that the process may accelerate the efficiency of the first aggregation, and shorten the time of the first aggregation, for example, if each target grid is traversed in sequence, after the 3 target grids in the circle of the first dotted line boundary in fig. 5 are deleted, the number of times of the first aggregation may be reduced, thereby accelerating the efficiency of the first aggregation.
Further, if the target grid included at the boundary of a circular region that is initially converged is not a complete grid, the target grid included in the circular region may be considered to be included in the circular region if the included area is greater than or equal to a predetermined area threshold, and the target grid not included in the circular region may be considered to be excluded in the circular region if the included area is less than the predetermined area threshold.
Further, if the target grid is located within both the circle bounded by the dashed line and the circle bounded by the solid line, the target grid may be optionally retained.
Example 3
One embodiment of the present application, referring to fig. 7, illustrates split aggregation comprising the steps of:
s310: and taking the average value of the longitude and the average value of the latitude of each grid center point in the connected sub-area as the connected center point of the corresponding connected sub-area.
Exemplarily, referring to fig. 8, the average of the longitudes and latitudes of the 6 grid center points in the connected sub-regions is used as the connected center point of the corresponding connected sub-regions, as shown by the cross point in fig. 8.
S320: and determining the maximum connected slice distance from the central point of each grid in the connected slice subarea to the central point of the connected slice.
The distance of each grid to the center point of the tile is calculated and the maximum tile distance, exemplary, is determined from the respective distances, and as shown in fig. 8, Dmax1 may represent the maximum tile distance.
S330: and if the maximum link distance is larger than the maximum distance threshold value, updating the number threshold value by using a number threshold increasing value.
The maximum distance threshold value can be set by combining the coverage scene of the base station and the coverage capability of the base station, preferably, the maximum distance threshold value should be larger than the convergence radius, and meanwhile, considering the problem of the coverage capability of the base station in the communication industry, the maximum distance threshold value should be smaller than or equal to 500 m. If the maximum distance threshold value of the contiguous sub-region is larger than the maximum distance threshold value, the number threshold value needs to be updated by using a preset number threshold increment value so as to split the contiguous sub-region.
The number threshold added value may be 1, that is, if the number threshold value corresponding to the initial aggregation is 4, the number threshold value may be updated by using the number threshold added value during the splitting and aggregation, that is, when the number threshold added value may be 1, the updated number threshold value may be 5, 6, 7, and 8 … … in sequence.
S340: and re-converging the grids in each continuous sub-area by using the updated number threshold value and the convergence radius and determining the discrete grids until the maximum continuous distance of each continuous sub-area is smaller than or equal to the maximum distance threshold value, wherein each continuous sub-area is used as an independent sub-area.
And re-converging the grids in each continuous sub-area by using the updated number threshold value and the convergence radius in sequence and determining the discrete grids until the maximum continuous distance of each continuous sub-area is smaller than or equal to the maximum distance threshold value, and taking each continuous sub-area as an independent sub-area.
For example, as shown in fig. 8, the grids in each connected sub-region are re-aggregated with a number threshold of 5 and the aggregation radius of 100m, and after aggregation, two connected sub-regions and a discrete grid a as shown in fig. 9 may be obtained, and further, it is determined whether the maximum connected distance between the two connected sub-regions is less than or equal to the maximum distance threshold, if still greater than the maximum distance threshold, the grids in each connected sub-region are re-aggregated with a number threshold of 6 and the aggregation radius of 100m, until the maximum connected distance between each connected sub-region is less than or equal to the maximum distance threshold, each connected sub-region is regarded as an independent sub-region.
S350: and sequentially adding qualified discrete grids to the adjacent independent sub-areas according to a preset discrete grid adding condition.
The discrete grid adding condition includes: the distance between the discrete grid and the central point of the independent sub-area to be added is smaller than a preset distance threshold; after the discrete grid is added to the independent sub-area to be added, the new density value of the independent sub-area to be added is less than or equal to the original density value; and the maximum distance value of the independent sub-area to be added after the discrete grid is added is smaller than or equal to the maximum distance threshold value.
Wherein the calculating of the density of the independent sub-region to be added comprises:
determining the number of grids, of which the distance from each grid in the independent sub-areas to be added to the central point of the independent sub-area to be added is smaller than the average distance of the independent sub-areas to be added; the density of the individual sub-regions to be added is calculated using the following formula:
ρ1＝num1*s1(Sa, p 1) density of the individual subareas to be added, s1And indicating a predetermined grid area, Sa indicating a divergence area corresponding to the independent sub-region to be added, and da-pi indicating an average distance of the independent sub-regions to be added.
Exemplarily, referring to fig. 9, if the distances between the discrete grid a and the center points of the two adjacent independent sub-regions are both smaller than a predetermined distance threshold, and the maximum distance value of the independent sub-region to which the discrete grid is added is smaller than or equal to the maximum distance threshold, it may be sequentially determined whether the new density values of the two independent sub-regions are reduced after the discrete grid a is added to the two independent sub-regions, if so, the two independent sub-regions are not scribed into the independent sub-regions, and if not, the new density values are not changed or increased, the two independent sub-regions may be scribed into the corresponding independent sub-regions. It can be understood that if the two independent sub-areas divided by the discrete grid a both satisfy the preset discrete grid adding condition, any independent sub-area can be divided alternatively.
Example 4
One embodiment of the present application, referring to FIG. 10, illustrates that merge aggregation includes the following steps:
s410: and determining the central point of the area to be merged corresponding to the longitude average value and the latitude average value of each grid central point in the independent sub-areas to be merged.
S420: and determining the maximum independent distance from the central point of each grid in the independent sub-regions to be combined to the central point of the region to be combined.
S430: and respectively determining the central points of the independent sub-areas to be combined.
S440: and determining the grid center point distance between each grid center point in the independent sub-areas to be combined and the center point of the corresponding independent sub-area.
S450: and determining the average grid center point distance of each independent sub-area to be combined according to the grid center point distance.
S460: determining a first ratio of the distance between the center points of the independent sub-areas to be combined to the sum of the distances of the center points of the average grids.
S470: and if the maximum independent distance is smaller than or equal to the maximum distance threshold value and the first ratio is smaller than the combination threshold ratio, combining the independent sub-regions to be combined.
Exemplarily, referring to fig. 11, a central point of a region to be merged corresponding to an average value of longitude and an average value of latitude of each grid central point in two independent sub-regions to be merged is F; calculating the distance from each grid in 2 independent sub-areas to be combined to the central point F of the area to be combined, and determining the maximum independent distance Dmax2 from each distance; respectively determining independent sub-region central points E and G of the 2 independent sub-regions; calculating the grid center point distance between each grid in the left independent subregion and the center point E of the corresponding independent subregion, and calculating the average grid center point distance d1 corresponding to the left independent subregion by using the grid center point distance in the left independent subregion; calculating the grid center point distance between each grid in the right independent subregion and the center point G of the corresponding independent subregion, and calculating the average grid center point distance d2 corresponding to the right independent subregion by using the grid center point distance in the right independent subregion; calculating a first ratio k1 ═ def/(d1+d2)，defIs the distance between the center points E and G of the individual sub-regions. Further, if the maximum independent distance Dmax2 is less than or equal to a preset maximum distance threshold value, and the first ratio k1 is less than a preset combining threshold ratio, combining the 2 independent sub-regions to be combined; if the maximum independent distance Dmax2 is greater than the preset maximum distance threshold value and the first ratio k1 is greater than the preset combination threshold ratio, the 2 independent sub-regions are not combined.
Optionally, a maximum distance threshold may be set according to the maximum coverage capability of the base station, and the maximum distance threshold may be 500 m; the combining threshold ratio can be customized according to requirements, and is used as a measurement standard for whether the independent sub-regions can be combined, the smaller the first ratio of the two independent sub-regions is, which indicates that the two independent sub-regions are more suitable for combining, and exemplarily, the combining threshold ratio may be 2.
Example 5
One embodiment of the present application, referring to FIG. 12, illustrates that scaling aggregation comprises the steps of:
s510: and taking the average value of the longitude and the average value of the latitude of each grid center point in each merging subarea as the merging center point of the corresponding merging subarea.
S520: and determining the maximum merging distance and the average merging distance from each grid central point in the merging subarea to the merging central point.
S530: determining a second ratio between the maximum combining distance and the average combining distance.
S540: and if the second ratio is larger than the discrete distance ratio threshold value, taking each grid in the corresponding merged sub-area as a discrete grid, and deleting the corresponding merged sub-area.
S550: and adding the qualified discrete grids to the adjacent merging subregions in sequence according to a preset discrete grid adding condition.
S560: and the rest merging subregions are used as the convergence window.
S570: and taking the rest grids in the rest merging subareas as the output grids.
Exemplarily, referring to fig. 13, if two independent sub-regions in fig. 13 satisfy the merge condition, fig. 13 can be regarded as one merge sub-region. Taking the average value of the longitude and the average value of the latitude of each grid central point in the merging subarea as a merging central point F of the corresponding merging subarea; determining the distances from the central points of the grids in the merging sub-region to the merging central point, determining the maximum merging distance Dmax3 from the distances, and calculating the average merging distance according to the distances
Determining the maximum combining distance Dmax3 and the average combining distance
And a second ratio k2 therebetween, it will be appreciated that,
the closer the second ratio k2 approaches 1, the more concentrated the merged sub-region, i.e., the farthest point is also within the divergence radius of the merged sub-region (the average merged distance of the merged sub-regions); if the second ratio k2 is greater than the discrete distance ratio threshold, each grid in the corresponding merged sub-region is used as a discrete grid, and the boundary of the corresponding merged sub-region is deleted, and the discrete distance ratio threshold may be set to 1.8.
Further, eligible discrete grids may be sequentially added to the adjacent merging sub-regions according to a predetermined discrete grid adding condition. The discrete grid adding condition includes: the distance between the discrete grid and the center point of the merging sub-region to be added is smaller than a preset distance threshold; after the discrete grid is added to the merging sub-area to be added, the new density value of the merging sub-area to be added is less than or equal to the original density value; and the maximum distance value of the merging sub-region to be added after the discrete grid is added is smaller than or equal to the maximum distance threshold value.
Wherein the calculating step of the density of the merged sub-region to be added comprises:
determining the number of grids, of which the distance from the center point of each grid in the merging sub-regions to be added to the center point of the merging sub-regions to be added is smaller than the average distance of the merging sub-regions to be added; the density of the merged sub-regions to be added is calculated using the following formula:
ρ2＝num2*s2/Sbρ 2 denotes the density of the merged subregion to be added, s2Representing a predetermined grid area, SbPresentation instrumentThe divergence area corresponding to the merged sub-region to be added, Sb＝db*db*π，dbRepresents the average distance of the merged sub-regions to be added.
Furthermore, traversing all the discrete grids, adding the discrete grids meeting the conditions to the adjacent merging sub-regions, deleting the discrete grids not meeting the conditions, taking the remaining merging sub-regions as the convergence window, and taking the remaining grids in the remaining merging sub-regions as the output grids.
Example 6
One embodiment of the present application, referring to fig. 14, illustrates that determining a convergence window boundary comprises the steps of:
s610: the boundary of the ith convergence window is determined.
And finding the output grid with the smallest ordinate from the ith convergence window, and marking the output grid as p 0. And calculating cosine values of included angles between connecting lines of the rest grids and the grid p0 in the ith convergence window and the x axis, and sequencing the grids from large to small according to the sine values of the grids to the p 0. The grid P1 corresponding to P0 and the maximum sine value is pushed into the stack, and then the calculation is started from the grid P2 corresponding to the second largest sine value, and whether the vector formed by the two grids P0 and P1 at the top of the stack and the grid P2 is rotated counterclockwise is calculated. If so, grid P2 is pushed onto the stack, otherwise the top element of the stack is pushed out. And after sequentially traversing all the output grids in the ith convergence window, outputting elements in the stack, namely the initial boundary of the ith convergence window.
S620: and drawing a jth ray corresponding to an mth starting point based on the direction from the mth starting point at the ith convergence window boundary to the central point of the jth convergence window by taking the output grid at the ith convergence window boundary as the starting point, wherein i is not equal to j, i is not more than N, j is not more than N, and N is the total number of the convergence windows.
S630: and if the jth ray corresponding to the mth starting point has odd intersection points with the boundary of the jth convergence window, deleting the mth starting point.
S640: and re-determining the boundary of the ith convergence window until the ray corresponding to each boundary point in the ith convergence window has even intersection points with the boundaries of other convergence windows.
S650: and determining the site position in the area to be planned according to the remaining output grids in each convergence window.
It is understood that, as shown in fig. 15, the boundaries of the N convergence windows may be determined by the above method, and then the central point in each boundary is determined, and the central point is taken as a station in the corresponding boundary range. Exemplarily, the longitude average and the latitude average of the center point of each grid in each boundary range are used as the center point of the corresponding boundary range.
Example 7
Referring to fig. 16, an embodiment of the present application shows a site planning apparatus 10 including an obtaining module 11, an aggregation module 12, a splitting module 13, a merging module 14, a scaling module 15, and a planning module 16.
The acquisition module 11 is configured to acquire each target grid in the area to be planned according to a predetermined site planning topic; the aggregation module 12 is configured to initially aggregate the target grids by using a predetermined initial aggregation parameter to filter discrete grids in the target grids and determine a plurality of connected sub-regions; a splitting module 13, configured to split and converge the grid in each connected sub-region by using a predetermined splitting and converging parameter, so as to split each connected sub-region and determine multiple independent sub-regions; a merging module 14, configured to merge the independent sub-regions by using a predetermined merging convergence parameter to determine a plurality of merged sub-regions, where each merged sub-region is formed by one or more independent sub-regions; a scaling module 15, configured to filter each merging sub-region by using a predetermined scaling convergence parameter, so as to determine a convergence window and an output grid in each convergence window; and the planning module 16 is configured to plan the site positions in the area to be planned according to the aggregation windows and the output grids.
The site planning apparatus 10 disclosed in this embodiment is configured to execute the site planning method according to the foregoing embodiment through the matching use of the obtaining module 11, the converging module 12, the splitting module 13, the merging module 14, the zooming module 15, and the planning module 16, and the implementation and beneficial effects related to the foregoing embodiment are also applicable to this embodiment, and are not described herein again.
The present application relates to a terminal device comprising a memory and a processor, the memory storing a computer program which, when run on the processor, performs the site planning method described herein.
The present application relates to a readable storage medium, in which a computer program is stored which, when run on a processor, performs the site planning method described herein.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, each functional module or unit in each embodiment of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention or a part of the technical solution that contributes to the prior art in essence can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a smart phone, a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention.
Claims (10)
1. A method for site planning, the method comprising:
acquiring each target grid in an area to be planned according to a preset site planning theme;
initially converging each target grid by using a preset initial convergence parameter to filter discrete grids in each target grid and determine a plurality of connected sub-areas;
splitting and converging the grids in each continuous sub-area by using a preset splitting and converging parameter to split each continuous sub-area and determine a plurality of independent sub-areas;
merging the independent sub-regions by using a preset merging convergence parameter to determine a plurality of merged sub-regions, wherein the merged sub-regions are formed by one or more independent sub-regions;
filtering each merging subarea by using a preset zooming convergence parameter to determine convergence windows and output grids in each convergence window;
and planning the site positions in the area to be planned according to the convergence windows and the output grids.
2. The site planning method according to claim 1, wherein the initial convergence parameters include a convergence radius and a threshold number of target grids in each convergence region, and wherein initially converging the target grids using the predetermined initial convergence parameters to filter discrete grids in the target grids and determine a plurality of connected sub-regions comprises:
drawing circles based on the convergence radius by taking each target grid as a circle center, and determining the number of the target grids in each circle, wherein the circle center is any point in the target grids;
judging whether the number of the target grids in each circle is larger than or equal to the number threshold value;
if the number is smaller than the number threshold value, filtering and deleting the target grids and the corresponding circular boundaries in the corresponding circles;
and determining a plurality of connected sub-areas in the area to be planned according to the remaining target grids in the circle which is larger than or equal to the number threshold value.
3. The station planning method according to claim 2, wherein the splitting and aggregating parameters include a maximum distance threshold value and a number threshold increase value, and the splitting and aggregating the grids in each contiguous sub-region by using the predetermined splitting and aggregating parameters to split and aggregate each contiguous sub-region and determine a plurality of independent sub-regions comprises:
taking the average value of the longitudes and the average value of the latitudes of the center points of each grid in the connected sub-areas as the connected center points of the corresponding connected sub-areas;
determining the maximum connected slice distance from each grid central point in the connected slice subarea to the connected slice central point;
if the maximum link distance is larger than the maximum distance threshold value, updating the number threshold value by using a number threshold increasing value;
re-converging the grids in each continuous sub-area by using the updated number threshold value and the convergence radius and determining a discrete grid until the maximum continuous distance of each continuous sub-area is smaller than or equal to the maximum distance threshold value, wherein each continuous sub-area is used as an independent sub-area;
and sequentially adding qualified discrete grids to the adjacent independent sub-areas according to a preset discrete grid adding condition.
4. The site planning method according to claim 3, wherein the merging aggregation parameter includes a merging threshold ratio, and the merging the individual sub-regions using the predetermined merging aggregation parameter to determine the plurality of merged sub-regions comprises:
determining the longitude average value of each grid center point in the independent subareas to be merged and the center point of the area to be merged corresponding to the latitude average value;
determining the maximum independent distance from each grid central point in the independent sub-areas to be merged to the central point of the area to be merged;
respectively determining the central points of the independent sub-areas to be combined;
determining the grid center point distance between each grid center point in the independent sub-areas to be combined and the center point of the corresponding independent sub-area;
determining the average grid center point distance of each independent sub-area to be combined according to each grid center point distance;
determining a first ratio of the distance between the center points of the independent sub-areas to be combined to the sum of the distances of the center points of the average grids;
and if the maximum independent distance is smaller than or equal to the maximum distance threshold value and the first ratio is smaller than the combination threshold ratio, combining the independent sub-regions to be combined.
5. The site planning method according to claim 4, wherein the scaling aggregation parameters include a discrete distance ratio threshold and a window density threshold, and wherein the filtering each merged sub-region using the predetermined scaling aggregation parameters to determine the aggregation windows and the output grids in each aggregation window comprises:
taking the average value of the longitude and the average value of the latitude of each grid central point in each merging subarea as the merging central point of the corresponding merging subarea;
determining the maximum merging distance and the average merging distance from each grid central point in the merging subarea to the merging central point;
determining a second ratio between the maximum combining distance and the average combining distance;
if the second ratio is larger than the discrete distance ratio threshold value, taking each grid in the corresponding merged sub-area as a discrete grid, and deleting the boundary of the corresponding merged sub-area;
sequentially adding the qualified discrete grids to the adjacent merging sub-regions according to a preset discrete grid adding condition;
the rest merging subregions are used as the convergence windows;
and taking the rest grids in the rest merging subareas as the output grids.
6. The site planning method according to claim 3 or 5, wherein the discrete grid adding condition comprises: the distance between the discrete grid and the central point of the region to be added is smaller than a preset distance threshold value; after the discrete grids are added to the area to be added, the new density value of the area to be added is greater than or equal to the original density value; the maximum distance value of the region to be added after the discrete grid is added is smaller than or equal to the maximum distance threshold value; the region to be added is a combined sub-region or an independent sub-region;
the calculating step of the density of the region to be added comprises the following steps:
determining the number of grids, of which the distance from each grid in the region to be added to the central point of the region to be added is smaller than the average distance of the region to be added;
the density of the region to be added is calculated using the following formula:
ρ＝num*s1s, p represents the density of the region to be added, S1And representing a predetermined grid area, S representing a divergence area corresponding to the region to be added, and d ═ d ×. pi, d representing an average distance of the region to be added.
7. The site planning method according to any one of claims 1 to 5, wherein the planning of the site locations in the area to be planned according to the respective convergence windows and the respective output grids comprises:
determining the boundary of the ith convergence window;
drawing a jth ray corresponding to an mth starting point based on the direction from the mth starting point at the ith convergence window boundary to the center point of the jth convergence window by taking an output grid at the ith convergence window boundary as the starting point, wherein i is not equal to j, i is not more than N, j is not more than N, and N is the total number of the convergence windows;
if the boundary of the jth ray corresponding to the mth starting point and the jth convergence window has odd intersection points, deleting the mth starting point;
re-determining the boundary of the ith convergence window until the ray corresponding to each boundary point in the ith convergence window has even intersection points with the boundaries of other convergence windows;
and determining the site position in the area to be planned according to the remaining output grids in each convergence window.
8. A site planning apparatus, the apparatus comprising:
the acquisition module is used for acquiring each target grid in the area to be planned according to a preset site planning theme;
the convergence module is used for initially converging each target grid by using a preset initial convergence parameter so as to filter discrete grids in each target grid and determine a plurality of connected sub-areas;
the splitting module is used for splitting and converging the grids in each continuous sub-area by using a preset splitting and converging parameter so as to split each continuous sub-area and determine a plurality of independent sub-areas;
the merging module is used for merging each independent sub-region by utilizing a preset merging convergence parameter to determine a plurality of merged sub-regions, and each merged sub-region consists of one or more independent sub-regions;
the zooming module is used for filtering each merging subarea by using a preset zooming convergence parameter so as to determine convergence windows and output grids in each convergence window;
and the planning module is used for planning the site positions in the area to be planned according to the convergence windows and the output grids.
9. A terminal device, characterized in that it comprises a memory and a processor, the memory storing a computer program which, when run on the processor, performs the site planning method according to any one of claims 1 to 7.
10. A readable storage medium, characterized in that it stores a computer program which, when run on a processor, performs the site planning method of any of claims 1 to 7.
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Inventor after: Huang Dongqing Inventor after: Pang Songtao Inventor after: Zhao Xueying Inventor after: Ning Shaolin Inventor after: Yuan Peiyan Inventor after: Zhang Junna Inventor after: Yang Zhao Inventor after: Jing Chaofan Inventor after: Yang Zilong Inventor after: Zheng Leiming Inventor after: Li Haonan Inventor after: Zhang Haibin Inventor after: Yang Dingyi Inventor after: Ren Kuo Inventor after: Qi Pengyong Inventor after: Wang Hui Inventor after: Zhao Xiaoyan Inventor after: Gao Zhitao Inventor after: Zhang Junru Inventor after: Li Xuelei Inventor before: Huang Dongqing Inventor before: Pang Songtao Inventor before: Zhao Xueying Inventor before: Ning Shaolin Inventor before: Yuan Peiyan Inventor before: Zhang Junna Inventor before: Yang Zhao Inventor before: Jing Chaofan Inventor before: Yang Zilong Inventor before: Zheng Leiming Inventor before: Li Haonan Inventor before: Zhang Haibin Inventor before: Yang Dingyi Inventor before: Ren Kuo Inventor before: Qi Pengyong Inventor before: Wang Hui Inventor before: Zhao Xiaoyan Inventor before: Gao Zhitao Inventor before: Zhang Junru Inventor before: Li Xuelei |