Scoring method and device of base station and related equipment

Abstract

The invention provides a base station scoring method and device and related equipment, and relates to the technical field of communication, and the method comprises the steps: obtaining a plurality of pieces of first data corresponding to a target base station; generating a plurality of pieces of second data according to the position information determined by the plurality of pieces of first data and the plurality of pieces of first data; determining a target scoring rule; and scoring the plurality of second data according to the target scoring rule to obtain a score value of the target base station. According to the method, the first data of different feature dimensions in the target base station are collected, so that data association is carried out according to the position information determined by the first data and the first data, and the second data corresponding to the station information are generated; and the multiple pieces of second data are scored through the target scoring rule matched with the regional position of the target base station, so that data of multiple dimensions and station information are considered when the base station is scored, and the accuracy of base station scoring is improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a base station scoring method, device and related equipment. Background Art

[0002] Current base station scoring methods primarily rely on input data related to the base station's geographic location, such as traffic, signal quality (e.g., RSRP), number of users, and user complaints. Because these existing scoring methods primarily rely on data from a single site dimension directly related to the base station's location, they ignore data errors caused by differences in data across multiple site dimensions when scoring base stations. This results in poor base station scoring accuracy. Summary of the Invention

[0003] The present invention provides a base station scoring method, device and related equipment, which solve the problem of poor accuracy of base station scoring in the prior art.

[0004] To solve the above problems, the present invention is achieved as follows: In a first aspect, an embodiment of the present application provides a base station scoring method, the method comprising: Acquire multiple first data corresponding to a target base station, where the multiple first data are communication data of multiple dimensions corresponding to the target base station, and different first data in the multiple first data correspond to different feature dimensions; generating a plurality of second data based on location information determined by the plurality of first data and the plurality of first data, wherein the location information includes site information associated with each first data in the plurality of first data, the plurality of second data corresponding one-to-one to the plurality of first data, and the second data being data obtained by associating and marking corresponding first data with corresponding site information; Determining a target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station; The plurality of second data are scored according to the target scoring rule to obtain a scoring value of the target base station.

[0005] Optionally, the multiple first data include: multiple base station data, multiple site data and multiple user data, and the base station data, the site data and the user data are different first data; Among them, the multiple base station data include basic information data of the target base station, the multiple site data include network quality data of multiple sites included in the communication range of the target base station, and the multiple user data include user perception data corresponding to multiple sites included in the communication range of the target base station.

[0006] Optionally, generating a plurality of second data according to the position information determined by the plurality of first data and the plurality of first data includes: determining the location information based on the plurality of site data and the plurality of user data; Based on the position information and the preset grid size, the plurality of user data are divided into grid areas to obtain a plurality of first divided data, wherein the plurality of first divided data correspond one-to-one to the plurality of user data; Based on the location information and the preset grid size, the plurality of site data are divided into grid areas to obtain a plurality of second divided data, wherein the plurality of second divided data correspond one-to-one to the plurality of site data; Based on the location information, the plurality of base station data are corrected to obtain a plurality of corrected data, wherein the plurality of corrected data correspond one-to-one to the plurality of base station data; The plurality of second data include the plurality of first divided data, the plurality of second divided data and the plurality of corrected data, wherein the first divided data, the second divided data and the corrected data are different second data.

[0007] Optionally, dividing the plurality of user data into grid areas based on the position information and a preset grid size to obtain a plurality of first divided data includes: Associating the plurality of user data with corresponding physical stations based on the plurality of user data and the location information to obtain a plurality of first associated data; Associating the plurality of user data with corresponding logical stations based on the plurality of user data and the location information to obtain a plurality of second associated data; Based on the position information and the preset grid size, the plurality of first associated data and the plurality of second associated data are divided into grid areas to obtain the plurality of first divided data.

[0008] Optionally, the correcting the plurality of base station data based on the location information to obtain a plurality of corrected data includes: Determine the latitude and longitude information corresponding to the plurality of base station data based on the location information; Determining, based on the latitude and longitude information and the data mapping relationship table, communication node data corresponding to the latitude and longitude information, the communication node data including physical station data and / or logical station data, the data mapping relationship table including a plurality of mapping data, wherein the mapping data includes a set of corresponding latitude and longitude information, physical station data, and logical station data; The plurality of base station data are corrected based on the communication node data to obtain the plurality of corrected data.

[0009] Optionally, scoring the plurality of second data according to the target scoring rule to obtain a scoring value of the target base station includes: Scoring the plurality of first divided data, the plurality of second divided data, and the plurality of corrected data according to the target scoring rule to obtain a scoring value of the target base station.

[0010] Optionally, determining a target scoring rule includes: Acquire multiple scoring rules, wherein different scoring rules correspond to different geographical locations; Determining the geographical location of the target base station; Based on the geographical location of the target base station, matching is performed among the multiple scoring rules to determine the target scoring rule.

[0011] Second invention, an embodiment of the present application provides a scoring device for a base station, the device comprising: an acquisition module, configured to acquire a plurality of first data corresponding to a target base station, wherein the plurality of first data are communication data of multiple dimensions corresponding to the target base station, and wherein different first data among the plurality of first data correspond to different feature dimensions; a generating module, configured to generate a plurality of second data based on location information determined by the plurality of first data and the plurality of first data, wherein the location information includes site information associated with each first data in the plurality of first data, the plurality of second data corresponding one-to-one to the plurality of first data, and the second data being data obtained by associating and marking corresponding first data with corresponding site information; a determination module, configured to determine a target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station; A scoring module is configured to score the plurality of second data according to the target scoring rule to obtain a scoring value of the target base station.

[0012] In a third aspect, the present application also provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method described in the first aspect above.

[0013] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in the method described in the first aspect above are implemented.

[0014] In a fifth aspect, the present application also provides a computer program product, comprising computer instructions, which, when executed by a processor, implement the steps in the method described in the first aspect above.

[0015] The present application provides a base station scoring method, apparatus, and related equipment, relating to the field of communication technology. The method includes: obtaining multiple first data corresponding to a target base station, the multiple first data being communication data of multiple dimensions corresponding to the target base station, and different first data in the multiple first data corresponding to different feature dimensions; generating multiple second data based on location information determined by the multiple first data and the multiple first data, the location information including site information associated with each first data in the multiple first data, the multiple second data corresponding one-to-one to the multiple first data, and the second data being data obtained by associating and marking the corresponding first data with the corresponding site information; determining a target scoring rule, the geographical location corresponding to the target scoring rule matching the geographical location of the target base station; scoring the multiple second data according to the target scoring rule to obtain a scoring value for the target base station. The present application collects first data of multiple different feature dimensions within the target base station, and then associates the location information determined by the multiple first data with the multiple first data to generate multiple second data corresponding to the site information, and scores the multiple second data using target scoring rules that match the geographical location of the target base station, thereby taking into account data of multiple dimensions and site information when scoring the base station, and improving the accuracy of the base station scoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for the description of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0017] Figure 1 A schematic diagram of a flow chart of a base station scoring method provided in an embodiment of the present application; Figure 2 The overall logic diagram of the system provided in the embodiment of the present application; Figure 3 A flowchart of the multi-dimensional business data conversion calculation and scoring provided in the embodiment of this application; Figure 4 A schematic diagram of the structure of a scoring device for a base station provided in an embodiment of the present application; Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0019] The terms "first", "second" etc. in the embodiments of the present application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. In addition, the terms "comprise" and "have" and any deformation thereof are intended to cover non-exclusive inclusions, such as, the process, method, system, product or equipment comprising a series of steps or units need not be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or that are intrinsic to these processes, methods, products or equipment. In addition, "and / or" is used in the present application to represent at least one of connected objects, such as A and / or B and / or C, and represents comprising independent A, independent B, independent C, and A and B all exist, B and C all exist, A and C all exist, and 7 situations that A, B and C all exist.

[0020] See also Figure 1 , Figure 1 This is a flow chart of the scoring method for a base station provided in an embodiment of the present application. Figure 1 As shown, the scoring method of the base station may include the following steps: Step 101: Acquire a plurality of first data corresponding to a target base station, where the plurality of first data are communication data of multiple dimensions corresponding to the target base station. Among the plurality of first data, different first data correspond to different feature dimensions.

[0021] In this embodiment, before scoring the target base station, it is necessary to obtain multiple first data corresponding to the target base station. The multiple first data are data of multiple different dimensions corresponding to the target base station. Specifically, each first data corresponds to a different feature dimension. Exemplarily, the feature dimensions corresponding to the first data may include basic information about the base station itself, network quality information of the site, user perception information, and the like, such as base station bandwidth data, latitude and longitude data, site traffic, site signal quality, service support data, and the like.

[0022] Step 102: Generate multiple second data based on the location information determined by the multiple first data and the multiple first data, wherein the location information includes the site information associated with each first data in the multiple first data, and the multiple second data correspond one-to-one to the multiple first data, and the second data is the data obtained by associating and marking the corresponding first data with the corresponding site information.

[0023] In this embodiment, location information of multiple first data is determined based on the acquired multiple first data, wherein the location information includes site information associated with each first data in the multiple first data. Specifically, the site information is relevant information of at least one site covered within the communication range of the base station, such as the site traffic, signal quality, number of users and other information.

[0024] Data association is performed based on the location information and multiple first data sets. Specifically, the site information associated with each first data set is associated and labeled with its corresponding first data set, thereby generating second data sets corresponding to each first data set, ultimately resulting in multiple second data sets. Compared to the first data, the second data is integrated with the site information associated with the first data set, making the first data more accurate and drawing on a wider range of data sources. Therefore, when scoring the target base station, the evaluation is more comprehensive.

[0025] Step 103: Determine a target scoring rule, where the geographical location corresponding to the target scoring rule matches the geographical location of the target base station.

[0026] In this embodiment, the geographical location corresponding to the target base station is determined based on the target base station. For example, due to significant differences in economic development and geographical location among provinces, different provinces also have different sensitivities to business data. Therefore, it is necessary to determine a target scoring rule that matches the target base station based on the geographical location corresponding to the target base station. For example, the target scoring rule includes a full score rule (T), a zero score rule (Y), a weight (Q), a full score threshold (M), a zero score threshold (O), a business data value (R), and the like, which are not specifically limited in this embodiment.

[0027] Step 104: Score the plurality of second data according to the target scoring rule to obtain a scoring value of the target base station.

[0028] In this embodiment, multiple second data are scored according to the matching target scoring rules to obtain a score value of the target base station, which is an overall evaluation of the target base station in multiple dimensions. Exemplarily, after obtaining the target scoring rules, if T is satisfied, the Q*100 value returned is (P); If Y is satisfied, the return value is 0 (P); If T and T are not met, the return value of (RO) / (MO)*Q*100 is (P); There will be multiple different types of score calculations for one second data, so one second data will contain multiple types of scores P1 P2 P3....

[0029] Then the current total score of the second data is Ptotal=P1+P2+P3+..... Therefore, compared with the existing technical solutions, this application has significant technical advantages in supporting business data of different site dimensions, adapting to the development conditions of different provinces, and more accurate calculation of site business data, and can better meet the needs of specific application scenarios.

[0030] The present application collects first data of multiple different feature dimensions within the target base station, and then associates the location information determined by the multiple first data with the multiple first data to generate multiple second data corresponding to the site information, and scores the multiple second data using target scoring rules that match the geographical location of the target base station, thereby taking into account data of multiple dimensions and site information when scoring the base station, and improving the accuracy of the base station scoring.

[0031] In some feasible implementations, optionally, the multiple first data include: multiple base station data, multiple site data, and multiple user data, and the base station data, the site data, and the user data are different first data; Among them, the multiple base station data include basic information data of the target base station, the multiple site data include network quality data of multiple sites included in the communication range of the target base station, and the multiple user data include user perception data corresponding to multiple sites included in the communication range of the target base station.

[0032] In this embodiment, the multiple first data are composed of multiple base station data, multiple site data and multiple user data, wherein the multiple base station data, multiple site data and multiple user data are different first data.

[0033] Specifically, the multiple base station data includes basic information data of the target base station, including latitude and longitude, bandwidth, frequency band, device type, province, and other data. The latitude and longitude are the longitude and latitude coordinates of the target base station. The bandwidth and frequency band are the bandwidth and frequency band that the target base station can cover. The device type is the type of communication device used by the target base station. The province is the location of the current target base station.

[0034] The multiple site data includes network quality data for multiple sites within the communication range of the target base station. This network quality data includes site-traffic, site-signal quality, site-number of users, and site-complaint data. Site-traffic is traffic data for a site. Site-signal quality is signal quality data for a site. Site-number of users is user data for a site. Site-complaints is user complaint data for a site.

[0035] The multiple user data include user perception data corresponding to multiple sites included in the communication range of the target base station, and the user perception data include logical station data, physical station data, and coverage area data. It should be noted that a physical station refers to a specific physical device or node, such as a computer, server, router, switch, etc. The characteristic of a physical station is that it can be actually touched and seen, and is usually a hardware facility. Physical station data is related data transmitted or generated by a physical station. A logical station refers to a virtual node defined in a network protocol or system. These logical stations do not necessarily correspond to specific physical devices and may be an abstract representation. Logical stations are generally used for data transmission and control in the network, involving logical addresses or identifiers at the protocol level, such as IP addresses, MAC addresses, etc. Logical station data is related data transmitted or generated by a logical station. Coverage area data is related data transmitted or generated within the communication coverage range of the target base station.

[0036] In this embodiment, the fusion application of multi-dimensional business data is achieved through base station data, site data and user data, thereby achieving measurement of the target base station through multiple dimensions.

[0037] Optionally, generating a plurality of second data according to the position information determined by the plurality of first data and the plurality of first data includes: determining the location information based on the plurality of site data and the plurality of user data; Based on the position information and the preset grid size, the plurality of user data are divided into grid areas to obtain a plurality of first divided data, wherein the plurality of first divided data correspond one-to-one to the plurality of user data; Based on the location information and the preset grid size, the plurality of site data are divided into grid areas to obtain a plurality of second divided data, wherein the plurality of second divided data correspond one-to-one to the plurality of site data; Based on the location information, the plurality of base station data are corrected to obtain a plurality of corrected data, wherein the plurality of corrected data correspond one-to-one to the plurality of base station data; The plurality of second data include the plurality of first divided data, the plurality of second divided data and the plurality of corrected data, wherein the first divided data, the second divided data and the corrected data are different second data.

[0038] In this embodiment, if Figure 2 As shown, Figure 2 This is the overall logic diagram of the system in this embodiment, wherein the audit data storage is used to store multiple base station data, the site dimension data storage is used to store multiple site data, and the other dimension data storage is used to store multiple user data. Specifically, the audit data storage interacts with the calculation module and is a type of data input to the calculation module. It stores data to be reviewed, including latitude and longitude, bandwidth, frequency band, device type, province, etc. The site dimension data manager interacts with the calculation module and is a type of data input to the calculation module. It stores business support data that has been associated with the site, such as site-traffic, site-signal quality, site-number of users, and site-complaints. The other dimension data storage interacts with the calculation module and is a type of data input to the calculation module. It stores some business support data that has not yet been associated with the site, such as logical station data, physical station data, and coverage area data.

[0039] In this embodiment, multiple base station data, multiple site data, and multiple user data are input into a calculation module for processing, resulting in multiple second data sets that are then scored by a scorer. Specifically, the calculation module interacts with a site dimension data storage, other dimension data storage, and an audit data storage, reads data from the data storage area, interacts with an output module, performs dimensional conversion, spatial association, and scoring on the input data, and then sends the data to the reviewer for review.

[0040] The dimensional data conversion part in the calculation module is responsible for converting business data of other dimensions into business data of site dimensions. The site data and base station association part in the calculation module is responsible for associating the site data with the grid area. The provincial rule library in the calculation module provides different scoring rules for different provinces, including full score rules, zero score rules, weights, full score / zero score thresholds, etc. The scorer in the calculation module finds the corresponding multi-dimensional spatial data (in grid units) based on the base station data and scores it in combination with the provincial rules. The auditor in the output module interacts with the calculation module to receive the grid scoring results output by the calculation module. The auditor audits the results according to the audit rules and stores the results in data.

[0041] Specifically, the location information is determined based on multiple site data and multiple user data, where the location information includes site information associated with each first data item in the multiple first data items. The preset grid size can be set based on actual conditions. In this embodiment, the grid size can be divided into a 50M*50M grid based on the cell's longitude and latitude information. Specifically, the division process involves processing multiple user data items, i.e., cell-dimensional data, and specifically includes: dividing the data into a 50M*50M grid based on the cell's longitude and latitude information. The service data (such as traffic, signal quality, number of users, etc.) of each cell is aggregated by grid to obtain service data (V) for each grid. The center longitude and latitude of each grid is calculated, converted to Mercator coordinates, and a unique ID50 identifier is generated. The longitude and latitude are fuzzified to obtain a long K value. A mapping relationship is established between the K value and multiple ID50s, and the service data and center longitude and latitude corresponding to each ID50 are recorded to form a Map set for subsequent use in searching for the nearest physical station.

[0042] Thus, the plurality of user data and the plurality of station data are divided into grid regions based on the location information and the preset grid size, thereby obtaining a plurality of first divided data and a plurality of second divided data. Furthermore, the plurality of base station data are corrected to obtain a plurality of corrected data. Thus, the plurality of second data includes a plurality of first divided data, a plurality of second divided data, and a plurality of corrected data, wherein the first divided data, the second divided data, and the positive data are different second data.

[0043] In this embodiment, for service data of different dimensions, site data and user data of different dimensions such as logical stations, physical stations, and coverage areas can be processed uniformly and accurately associated with base station data.

[0044] Optionally, dividing the plurality of user data into grid areas based on the position information and a preset grid size to obtain a plurality of first divided data includes: Associating the plurality of user data with corresponding physical stations based on the plurality of user data and the location information to obtain a plurality of first associated data; Associating the plurality of user data with corresponding logical stations based on the plurality of user data and the location information to obtain a plurality of second associated data; Based on the position information and the preset grid size, the plurality of first associated data and the plurality of second associated data are divided into grid areas to obtain the plurality of first divided data.

[0045] In this embodiment, a plurality of user data and location information are associated to obtain a plurality of first associated data associating the plurality of user data with the corresponding physical stations, for example, Figure 3 As shown, Figure 3 This is a flowchart for converting and calculating scores for multi-dimensional business data. Based on multiple user data and location information, the user data is associated with the corresponding physical stations to obtain multiple first-level associated data. Specifically, a physical station contains multiple cells. The process for converting a physical station into cell-level data is as follows: The cell information corresponding to a physical station is merged. The center longitude and latitude of the physical station are calculated, and the longitude and latitude of ID50 are fuzzified to obtain a long value K. This generates multiple cell-level data.

[0046] Based on multiple user data and location information, the multiple user data are associated with corresponding logical stations to generate multiple pieces of second associated data. Specifically, a logical station may contain multiple physical stations, and a physical station may also include multiple cells under different logical stations. Therefore, the data at the logical station level requires further processing, including merging all cell stations under a logical station. The service data for each cell is calculated as follows: logical station service data divided by the number of cells under the logical station. This generates multiple pieces of cell-level data.

[0047] Thus, based on the location information and the preset grid size, the multiple first associated data and the multiple second associated data are divided into grid areas to obtain multiple first divided data. Specifically, the coverage area and the work parameter information are merged to obtain all cell data within the coverage area. These cell data are rasterized, and the physical station ID50 of multiple grids in the coverage area is obtained through a hash algorithm. The number of physical stations (N) in the current coverage area is determined: if N is less than or equal to 2, all the business data of these physical stations are set as the business data of the coverage area. If N is greater than 2, the business data of each physical station is calculated according to the following formula: current physical station business data = (number of cells to which the current physical station belongs / total number of cells) * coverage area business data. Thus, physical station data corresponding to one or more coverage areas is finally generated. For the business support data of the site dimension that already contains spatial information such as longitude and latitude, such as complaint data, the longitude and latitude information is divided into a 50M*50M grid and then the business data is aggregated, i.e., multiple first divided data.

[0048] Optionally, the correcting the plurality of base station data based on the location information to obtain a plurality of corrected data includes: Determine the latitude and longitude information corresponding to the plurality of base station data based on the location information; Determining, based on the latitude and longitude information and the data mapping relationship table, communication node data corresponding to the latitude and longitude information, the communication node data including physical station data and / or logical station data, the data mapping relationship table including a plurality of mapping data, wherein the mapping data includes a set of corresponding latitude and longitude information, physical station data, and logical station data; The plurality of base station data are corrected based on the communication node data to obtain the plurality of corrected data.

[0049] In this embodiment, multiple base station data are corrected based on latitude and longitude information and a data mapping table to obtain the multiple corrected data. First, the latitude and longitude information corresponding to the multiple base station data is obtained. A fuzzy K value is calculated based on the latitude and longitude information. GIS technology is used to calculate multiple K values within a 1000-meter range. The physical station data corresponding to these K values is searched from the data mapping sets for each service type established in steps A1-A4. Based on the latitude and longitude distance between the physical station and the base station data, the physical station closest to the base station data is found. Various types of service data (traffic, signal quality, number of users, etc.) of the nearest physical station are assigned to the corresponding dimensions of the base station data. Through this process, the nearest physical station can be quickly found based on the fuzzy latitude and longitude of the base station data, and its service data can be associated with the base station data. This ensures that the base station data accurately represents the actual situation at the current location and provides accurate input data for subsequent scoring calculations.

[0050] By fuzzifying the latitude and longitude information of base station data and establishing a mapping set, the physical site closest to the base station data can be quickly found, thereby improving the accuracy of data matching.

[0051] Optionally, scoring the plurality of second data according to the target scoring rule to obtain a scoring value of the target base station includes: Scoring the plurality of first divided data, the plurality of second divided data, and the plurality of corrected data according to the target scoring rule to obtain a scoring value of the target base station.

[0052] In this embodiment, multiple first divided data, multiple second divided data and multiple corrected data are scored according to the determined target scoring rules to obtain the scoring value of the target base station, wherein the multiple second data are determined as multiple first divided data, multiple second divided data and multiple corrected data, realizing a scoring system that integrates multiple data sources such as site dimension, logical station dimension, physical station dimension and coverage area dimension, which can more comprehensively reflect the actual situation of the base station.

[0053] Optionally, determining a target scoring rule includes: Acquire multiple scoring rules, wherein different scoring rules correspond to different geographical locations; Determining the geographical location of the target base station; Based on the geographical location of the target base station, matching is performed among the multiple scoring rules to determine the target scoring rule.

[0054] In this embodiment, different provinces are used as an example for different geographical locations. In this embodiment, different scoring rules are set for multiple different identities. When scoring a target base station, the province where the target base station is located is determined, and thus a target scoring rule can be determined based on the province. Thus, by supporting flexible configuration of scoring rules, weights, and thresholds for different provinces, targeted scoring can be performed based on the economic development levels and geographical conditions of different regions. This adaptability greatly improves the system's applicability across different provinces, and has broad application potential.

[0055] The present application collects first data of multiple different feature dimensions within the target base station, and then associates the location information determined by the multiple first data with the multiple first data to generate multiple second data corresponding to the site information, and scores the multiple second data using target scoring rules that match the geographical location of the target base station, thereby taking into account data of multiple dimensions and site information when scoring the base station, and improving the accuracy of the base station scoring.

[0056] See also Figure 4 , Figure 4 This is a structural diagram of the scoring device of the base station provided in the embodiment of the present application. Figure 4 As shown, the scoring device 400 of the base station includes: An acquisition module 410 is configured to acquire a plurality of first data corresponding to a target base station, where the plurality of first data are communication data of multiple dimensions corresponding to the target base station, and different first data in the plurality of first data correspond to different feature dimensions; a generating module 420 configured to generate a plurality of second data based on location information determined by the plurality of first data and the plurality of first data, wherein the location information includes site information associated with each first data in the plurality of first data, the plurality of second data corresponding one-to-one to the plurality of first data, and the second data being data obtained by associating and marking corresponding first data with corresponding site information; A determination module 430 is configured to determine a target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station; The scoring module 440 is configured to score the plurality of second data according to the target scoring rule to obtain a scoring value of the target base station.

[0057] Optionally, the multiple first data include: multiple base station data, multiple site data and multiple user data, and the base station data, the site data and the user data are different first data; Among them, the multiple base station data include basic information data of the target base station, the multiple site data include network quality data of multiple sites included in the communication range of the target base station, and the multiple user data include user perception data corresponding to multiple sites included in the communication range of the target base station.

[0058] Optionally, the generating module 420 includes: A first determining submodule, configured to determine the location information based on the plurality of site data and the plurality of user data; A first division submodule is configured to divide the plurality of user data into grid areas based on the position information and a preset grid size to obtain a plurality of first division data, wherein the plurality of first division data corresponds one-to-one to the plurality of user data; A second division submodule is configured to divide the plurality of site data into grid areas based on the location information and the preset grid size to obtain a plurality of second division data, wherein the plurality of second division data corresponds one-to-one to the plurality of site data; a correction submodule, configured to correct the plurality of base station data based on the location information to obtain a plurality of correction data, wherein the plurality of correction data corresponds one-to-one to the plurality of base station data; The plurality of second data include the plurality of first divided data, the plurality of second divided data and the plurality of corrected data, wherein the first divided data, the second divided data and the corrected data are different second data.

[0059] Optionally, the first division submodule includes: a first associating unit, configured to associate the plurality of user data with corresponding physical stations based on the plurality of user data and the location information to obtain a plurality of first associated data; a second associating unit, configured to associate the plurality of user data with corresponding logical stations based on the plurality of user data and the location information to obtain a plurality of second associated data; The division unit is configured to divide the plurality of first associated data and the plurality of second associated data into grid areas based on the position information and the preset grid size to obtain the plurality of first divided data.

[0060] Optionally, modify submodules, including: A first determining unit, configured to determine the longitude and latitude information corresponding to the plurality of base station data based on the location information; a second determining unit, configured to determine, based on the latitude and longitude information and a data mapping relationship table, communication node data corresponding to the latitude and longitude information, the communication node data including physical station data and / or logical station data, the data mapping relationship table including a plurality of mapping data, wherein the mapping data includes a set of corresponding latitude and longitude information, physical station data, and logical station data; A correction unit is used to correct the multiple base station data based on the communication node data to obtain the multiple corrected data.

[0061] Optionally, the scoring module 440 includes: A scoring submodule is configured to score the plurality of first divided data, the plurality of second divided data, and the plurality of corrected data according to the target scoring rule to obtain a scoring value of the target base station.

[0062] Optionally, the determining module 430 includes: An acquisition submodule, configured to acquire a plurality of scoring rules, wherein different scoring rules correspond to different geographical locations; A second determining submodule is used to determine the geographical location of the target base station; The third determining submodule is configured to match the plurality of scoring rules based on the geographical location of the target base station to determine the target scoring rule.

[0063] The present application collects first data of multiple different feature dimensions within the target base station, and then associates the location information determined by the multiple first data with the multiple first data to generate multiple second data corresponding to the site information, and scores the multiple second data using target scoring rules that match the geographical location of the target base station, thereby taking into account data of multiple dimensions and site information when scoring the base station, and improving the accuracy of the base station scoring.

[0064] The present application also provides an electronic device. Figure 5 , the electronic device may include a processor 501, a memory 502, and a program 5021 stored in the memory 502 and executable on the processor 501.

[0065] When the program 5021 is executed by the processor 501, it can achieve Figure 1 Any step in the corresponding method embodiment: Acquire multiple first data corresponding to a target base station, where the multiple first data are communication data of multiple dimensions corresponding to the target base station, and different first data in the multiple first data correspond to different feature dimensions; generating a plurality of second data based on location information determined by the plurality of first data and the plurality of first data, wherein the location information includes site information associated with each first data in the plurality of first data, the plurality of second data corresponding one-to-one to the plurality of first data, and the second data being data obtained by associating and marking corresponding first data with corresponding site information; Determining a target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station; The plurality of second data are scored according to the target scoring rule to obtain a scoring value of the target base station.

[0066] Optionally, the multiple first data include: multiple base station data, multiple site data and multiple user data, and the base station data, the site data and the user data are different first data; Among them, the multiple base station data include basic information data of the target base station, the multiple site data include network quality data of multiple sites included in the communication range of the target base station, and the multiple user data include user perception data corresponding to multiple sites included in the communication range of the target base station.

[0067] Optionally, generating a plurality of second data according to the position information determined by the plurality of first data and the plurality of first data includes: determining the location information based on the plurality of site data and the plurality of user data; Based on the position information and the preset grid size, the plurality of user data are divided into grid areas to obtain a plurality of first divided data, wherein the plurality of first divided data correspond one-to-one to the plurality of user data; Based on the location information and the preset grid size, the plurality of site data are divided into grid areas to obtain a plurality of second divided data, wherein the plurality of second divided data correspond one-to-one to the plurality of site data; Based on the location information, the plurality of base station data are corrected to obtain a plurality of corrected data, wherein the plurality of corrected data correspond one-to-one to the plurality of base station data; The plurality of second data include the plurality of first divided data, the plurality of second divided data and the plurality of corrected data, wherein the first divided data, the second divided data and the corrected data are different second data.

[0068] Optionally, dividing the plurality of user data into grid areas based on the position information and a preset grid size to obtain a plurality of first divided data includes: Associating the plurality of user data with corresponding physical stations based on the plurality of user data and the location information to obtain a plurality of first associated data; Associating the plurality of user data with corresponding logical stations based on the plurality of user data and the location information to obtain a plurality of second associated data; Based on the position information and the preset grid size, the plurality of first associated data and the plurality of second associated data are divided into grid areas to obtain the plurality of first divided data.

[0069] Optionally, the correcting the plurality of base station data based on the location information to obtain a plurality of corrected data includes: Determine the latitude and longitude information corresponding to the plurality of base station data based on the location information; Determining, based on the latitude and longitude information and the data mapping relationship table, communication node data corresponding to the latitude and longitude information, the communication node data including physical station data and / or logical station data, the data mapping relationship table including a plurality of mapping data, wherein the mapping data includes a set of corresponding latitude and longitude information, physical station data, and logical station data; The plurality of base station data are corrected based on the communication node data to obtain the plurality of corrected data.

[0070] Optionally, scoring the plurality of second data according to the target scoring rule to obtain a scoring value of the target base station includes: Scoring the plurality of first divided data, the plurality of second divided data, and the plurality of corrected data according to the target scoring rule to obtain a scoring value of the target base station.

[0071] Optionally, determining a target scoring rule includes: Acquire multiple scoring rules, wherein different scoring rules correspond to different geographical locations; Determining the geographical location of the target base station; Based on the geographical location of the target base station, matching is performed among the multiple scoring rules to determine the target scoring rule.

[0072] The present application collects first data of multiple different feature dimensions within the target base station, and then associates the location information determined by the multiple first data with the multiple first data to generate multiple second data corresponding to the site information, and scores the multiple second data using target scoring rules that match the geographical location of the target base station, thereby taking into account data of multiple dimensions and site information when scoring the base station, and improving the accuracy of the base station scoring.

[0073] The present application also provides a computer-readable storage medium having a computer program stored thereon. When executed by a processor, the computer program implements the various processes of the above-mentioned base station scoring method embodiment and can achieve the same technical effect. To avoid repetition, the details are not described here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0074] An embodiment of the present application further provides a computer program product, which is stored in a storage medium. The computer program product is executed by at least one processor to implement the various processes of the above-mentioned base station scoring method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0075] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0076] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a more preferred embodiment. Based on this understanding, the technical solution of this application, or the part that contributes to the existing technology, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of this application.

[0077] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A scoring method for a base station, characterized in that: The method comprises: Acquire multiple first data corresponding to a target base station, where the multiple first data are communication data of multiple dimensions corresponding to the target base station, and different first data in the multiple first data correspond to different feature dimensions; generating a plurality of second data based on location information determined by the plurality of first data and the plurality of first data, wherein the location information includes site information associated with each first data in the plurality of first data, the plurality of second data corresponding one-to-one to the plurality of first data, and the second data being data obtained by associating and marking corresponding first data with corresponding site information; Determining a target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station; The plurality of second data are scored according to the target scoring rule to obtain a scoring value of the target base station.

2. The method according to claim 1, characterized in that The plurality of first data includes: a plurality of base station data, a plurality of site data and a plurality of user data, wherein the base station data, the site data and the user data are different first data; Among them, the multiple base station data include basic information data of the target base station, the multiple site data include network quality data of multiple sites included in the communication range of the target base station, and the multiple user data include user perception data corresponding to multiple sites included in the communication range of the target base station.

3. The method according to claim 2, characterized in that Generating a plurality of second data according to the position information determined by the plurality of first data and the plurality of first data includes: determining the location information based on the plurality of site data and the plurality of user data; Based on the position information and the preset grid size, the plurality of user data are divided into grid areas to obtain a plurality of first divided data, wherein the plurality of first divided data correspond one-to-one to the plurality of user data; Based on the location information and the preset grid size, the plurality of site data are divided into grid areas to obtain a plurality of second divided data, wherein the plurality of second divided data correspond one-to-one to the plurality of site data; Based on the location information, the plurality of base station data are corrected to obtain a plurality of corrected data, wherein the plurality of corrected data correspond one-to-one to the plurality of base station data; The plurality of second data include the plurality of first divided data, the plurality of second divided data and the plurality of corrected data, wherein the first divided data, the second divided data and the corrected data are different second data.

4. The method according to claim 3, characterized in that The grid area division of the plurality of user data based on the position information and the preset grid size to obtain a plurality of first divided data includes: Associating the plurality of user data with corresponding physical stations based on the plurality of user data and the location information to obtain a plurality of first associated data; Associating the plurality of user data with corresponding logical stations based on the plurality of user data and the location information to obtain a plurality of second associated data; Based on the position information and the preset grid size, the plurality of first associated data and the plurality of second associated data are divided into grid areas to obtain the plurality of first divided data.

5. The method according to claim 3, characterized in that The correcting the plurality of base station data based on the location information to obtain a plurality of corrected data includes: Determine the latitude and longitude information corresponding to the plurality of base station data based on the location information; Determining, based on the latitude and longitude information and the data mapping relationship table, communication node data corresponding to the latitude and longitude information, the communication node data including physical station data and / or logical station data, the data mapping relationship table including a plurality of mapping data, wherein the mapping data includes a set of corresponding latitude and longitude information, physical station data, and logical station data; The plurality of base station data are corrected based on the communication node data to obtain the plurality of corrected data.

6. The method according to claim 3, characterized in that Scoring the plurality of second data according to the target scoring rule to obtain a scoring value of the target base station includes: Scoring the plurality of first divided data, the plurality of second divided data, and the plurality of corrected data according to the target scoring rule to obtain a scoring value of the target base station.

7. The method according to any one of claims 1 to 6, characterized in that The target scoring rule is determined, including: Acquire multiple scoring rules, wherein different scoring rules correspond to different geographical locations; Determining the geographical location of the target base station; Based on the geographical location of the target base station, matching is performed among the multiple scoring rules to determine the target scoring rule.

8. A scoring device for a base station, characterized in that: The device comprises: an acquisition module, configured to acquire a plurality of first data corresponding to a target base station, wherein the plurality of first data are communication data of multiple dimensions corresponding to the target base station, and wherein different first data among the plurality of first data correspond to different feature dimensions; a generating module, configured to generate a plurality of second data based on location information determined by the plurality of first data and the plurality of first data, wherein the location information includes site information associated with each first data in the plurality of first data, the plurality of second data corresponding one-to-one to the plurality of first data, and the second data being data obtained by associating and marking corresponding first data with corresponding site information; a determination module, configured to determine a target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station; A scoring module is configured to score the plurality of second data according to the target scoring rule to obtain a scoring value of the target base station.

9. An electronic device, characterized in that: include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which implements the steps of the method according to any one of claims 1 to 7 when executed by a processor.

11. A computer program product, characterized in that The method comprises computer instructions, which, when executed by a processor, implement the steps of the method according to any one of claims 1 to 7.

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