Method, apparatus and device for determining transport network deployment information

Abstract

The embodiment of the application provides a method, device and equipment for determining transmission network deployment information, the method for determining transmission network deployment information comprises the following steps: acquiring B-domain data, O-domain data and geographic information system (GIS) layer data in at least one preset area, and inputting the B-domain data, the O-domain data and the GIS layer data into a preset scoring model to obtain the area score of each area; and according to the area score, determining the transmission network deployment information of the preset area, so that the transmission network of the preset area accurately matches the network demand of the user, without relying on personal experience, and the deployment efficiency of the transmission network is improved.

Description

Technical Field

[0001] This application belongs to the field of network planning technology, and in particular relates to a method, apparatus and equipment for determining network deployment information. Background Technology

[0002] With the development of internet technology, mobile, home, government and enterprise, and emerging market services are also growing rapidly, carrying these services within the transmission network and using a single network as a unified service carrier. Faced with the rapidly evolving range of services, a microgrid approach is adopted to divide the planned area into multiple microgrids. That is, the planned area is divided into multiple pre-defined areas according to preset conditions. Fiber optic cabling junction facilities are deployed to connect to the transmission network based on the network needs of users in each pre-defined area. However, when other users in the same pre-defined area request access to the transmission network, the previously deployed fiber optic cabling junction facilities may be unable to connect these users' cables due to distance, making it difficult to expand capacity in a short time and support service development. Therefore, how to pre-deploy fiber optic cabling junction facilities based on potential user needs is a key aspect of transmission network planning.

[0003] Currently, attribute information for a pre-defined area is transmitted via email, and then this information is manually reviewed. Based on personal experience, the pre-defined areas to be deployed are determined, and fiber optic cabling facilities are pre-deployed in these areas. Because the process of determining the pre-defined areas relies on personal experience, it is not only inefficient but also difficult to consider comprehensively, resulting in pre-defined areas that are unlikely to accurately match the user's network needs. Summary of the Invention

[0004] This application provides a method, apparatus, and device for determining transmission network deployment information, which enables the transmission network to be deployed in a preset area to accurately match the user's network needs without relying on personal experience, thereby improving the deployment efficiency of the transmission network.

[0005] In a first aspect, embodiments of this application provide a method for determining transmission network deployment information, the method comprising: acquiring B-domain data, O-domain data and Geographic Information System (GIS) layer data in at least one preset area;

[0006] Input B-domain data, O-domain data and GIS layer data into the preset scoring model to obtain a regional score for each preset region in at least one preset region. The regional score is used to assess the network resource demand of users in each preset region.

[0007] Based on the regional score, determine the transmission network deployment information in at least one preset region.

[0008] In some possible implementations, the GIS layer data includes user coordinate data and preset area coordinate data; by inputting the B-domain data, O-domain data, and GIS layer data into a preset scoring model, a regional score for each preset area is obtained, including:

[0009] Based on preset classification conditions, labels are created for user coordinate data and preset area coordinate data, resulting in labeled user coordinate data and labeled preset area coordinate data.

[0010] Based on the pre-acquired geographic location information, the tag user coordinate data and the tag preset area coordinate data are calibrated to obtain standard coordinate data;

[0011] The B-domain data, O-domain data, and standard coordinate data are overlaid and merged to obtain the fused data;

[0012] The fused data is input into a preset scoring model to obtain a regional score for each preset region in at least one preset region.

[0013] In some possible implementations, at least one preset area includes at least one user; B-domain data, O-domain data, and GIS layer data are input into a preset scoring model to obtain a regional score for each preset area within at least one preset area, including:

[0014] Input B-domain data, O-domain data and GIS layer data into a preset scoring model to obtain an individual score for each user in at least one user group. The individual score is used to assess the network resource demand of each user in at least one user group.

[0015] Based on user coordinate data and preset area coordinate data, determine the target user in each preset area of ​​at least one preset area;

[0016] The individual scores corresponding to the target users in each of the at least one preset region are summed to obtain the regional score for each of the at least one preset region.

[0017] In some possible implementations, based on regional scoring, transmission network deployment information in at least one preset region is determined, including:

[0018] Arrange the regional scores in descending order to obtain the regional score ranking table;

[0019] Based on the regional scoring and ranking table, determine the transmission network deployment information in at least one preset region.

[0020] In some possible implementations, before inputting B-domain data, O-domain data, and GIS layer data into a preset scoring model to obtain a regional score for each preset region in at least one preset region, the method further includes:

[0021] Obtain sample data, which includes B-domain data, O-domain data, and GIS layer data;

[0022] The weight values ​​corresponding to B-domain data, O-domain data, and GIS layer data are calculated from different dimensions to obtain the preset scoring model.

[0023] Secondly, embodiments of this application provide an apparatus for determining network deployment information, the apparatus comprising:

[0024] The acquisition module is used to acquire B-domain data, O-domain data, and GIS layer data from at least one preset area.

[0025] The input module is used to input B-domain data, O-domain data and GIS layer data into the preset scoring model to obtain the regional score of each preset region in at least one preset region. The regional score is used to evaluate the network resource demand of users in each preset region.

[0026] The planning module is used to determine the transmission network deployment information in at least one preset area based on the area score.

[0027] In some possible implementations, the GIS layer data includes user coordinate data and preset area coordinate data; the input module is specifically used for:

[0028] Based on preset classification conditions, labels are created for user coordinate data and preset area coordinate data, resulting in labeled user coordinate data and labeled preset area coordinate data.

[0029] Based on the pre-acquired geographic location information, the tag user coordinate data and the tag preset area coordinate data are calibrated to obtain standard coordinate data;

[0030] The B-domain data, O-domain data, and standard coordinate data are overlaid and merged to obtain the fused data;

[0031] The fused data is input into a preset scoring model to obtain a regional score for each preset region in at least one preset region.

[0032] In some possible implementations, at least one preset area includes at least one user; the input module is specifically used for:

[0033] Input B-domain data, O-domain data and GIS layer data into a preset scoring model to obtain an individual score for each user in at least one user group. The individual score is used to assess the network resource demand of each user in at least one user group.

[0034] Based on user coordinate data and preset area coordinate data, determine the target user in each preset area of ​​at least one preset area;

[0035] The individual scores corresponding to the target users in each of the at least one preset region are summed to obtain the regional score for each of the at least one preset region.

[0036] Thirdly, embodiments of this application provide a transmission network deployment information determination device, the device comprising: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the transmission network deployment information determination method in the first aspect or any implementation thereof.

[0037] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the method for determining transmission network deployment information in the first aspect or any implementation thereof.

[0038] The method, apparatus, device, and computer-readable storage medium for determining transmission network deployment information provided in this application embodiment acquire B-domain data, O-domain data, and GIS layer data in at least one preset area, input the B-domain data, O-domain data, and GIS layer data into a preset scoring model to obtain a regional score for each area, and determine the transmission network deployment information for the preset area based on the regional score. This enables the transmission network in the preset area to accurately match the user's network needs without relying on personal experience, thereby improving the deployment efficiency of the transmission network. Attached Figure Description

[0039] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart illustrating a method for determining transmission network deployment information provided in an embodiment of this application;

[0041] Figure 2 This is a schematic diagram of the structure of a transmission network deployment information determination device provided in an embodiment of this application;

[0042] Figure 3 This is a schematic diagram of the structure of a transmission network deployment information determination device provided in an embodiment of this application. Detailed Implementation

[0043] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0044] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0045] Currently, during the transmission network planning process, attribute information within a pre-defined area is transmitted via email. This attribute information includes user information, service information, and coordinate information. Manually reviewing this attribute information is necessary, and data changes require repeated email resending, necessitating further manual reorganization. Combining this attribute information with visual observation and personal experience on a map, pre-deployment of fiber optic cable junction facilities within these areas, and finally, outputting the transmission network deployment information, is crucial.

[0046] However, manually processing massive amounts of data is complex, easily leading to data chaos, redundant calculations, and low efficiency. Furthermore, information coordination between different levels is difficult, and pre-deployed fiber optic junction facilities, based on personal experience and visual judgment, cannot accurately match users' network needs.

[0047] To address the problems of existing technologies, embodiments of this application provide a method, apparatus, device, and computer-readable storage medium for determining transmission network deployment information. In this embodiment, B-domain data, O-domain data, and Geographic Information System (GIS) layer data from at least one preset area are acquired. The B-domain data, O-domain data, and GIS layer data are then input into a preset scoring model to obtain a regional score for each area. Based on the regional scores, the transmission network deployment information for the preset area is determined. This ensures that the transmission network for the preset area accurately matches the user's network needs, eliminating reliance on personal experience and improving the deployment efficiency of the transmission network.

[0048] The method for determining transmission network deployment information provided in the embodiments of this application will be introduced first below.

[0049] Figure 1 A flowchart illustrating a method for determining transmission network deployment information according to an embodiment of this application is shown. Figure 1 As shown, the method may include the following steps:

[0050] S110, acquire B-domain data, O-domain data and GIS layer data from at least one preset area.

[0051] In the process of planning a transmission network, the area to be planned is usually divided into multiple small areas according to preset conditions. These small areas are called preset areas, or microgrids.

[0052] B-domain data includes user data and business data. User data includes user names, consumption habits, terminal data, business content data, and target audience data. Business data includes voice usage data, SMS usage data, data usage data, and subscription package data.

[0053] O-domain data includes network data, specifically including International Mobile Subscriber Identity (IMSI) information, Reference Signal Receiving Power (RSRP) information, occupied cell information, network resources, signaling, alarms, faults, and other data.

[0054] Geographic Information System (GIS) layer data includes data from different layers. For example, GIS layers include road layers and building layers, and GIS layer data includes road data and building data.

[0055] B-domain data can be collected from the billing, customer service, accounting, settlement, and business analysis systems of business departments or third-party enterprises. O-domain data can be obtained from the operator's resource database, and GIS layer data for the area to be planned can be obtained from existing information systems and databases. The acquisition of B-domain data, O-domain data, and GIS layer data is used to determine transmission network deployment information. Specifically, the transmission network deployment information assists the operator in planning the transmission network by deploying fiber optic cable junction facilities within the predetermined area.

[0056] S120, input B-domain data, O-domain data and GIS layer data into the preset scoring model to obtain the regional score of each preset region in at least one preset region. The regional score is used to evaluate the network resource demand of users in each preset region.

[0057] The preset scoring model is a pre-trained scoring model that can assess the network resource needs of users in each preset area based on B-domain data, O-domain data, and GIS layer data. Users in the preset area can be individuals, businesses, schools, hospitals, hotels, etc.

[0058] By inputting B-domain data, O-domain data, and GIS layer data into a preset scoring model, a regional score is obtained for each preset area, which is then used to assess the network resource needs of users within each preset area. Only by understanding the network resource needs of users within the area to be planned can the transmission network be accurately planned, resource waste reduced, network resources rationally invested and deployed, and benefits maximized.

[0059] S130, Based on the regional score, determine the transmission network deployment information in at least one preset region.

[0060] During the transmission network planning process, fiber optic junction facilities are not deployed in all pre-defined areas within the planning area. Instead, based on the area scoring, the network resource needs of users within the pre-defined area are understood, and the deployment of fiber optic junction facilities is carried out by comprehensively considering the investment amount and expected revenue.

[0061] For regional scoring at different stages, different colors can be used to render and display the data on a layer, distinguishing between preset areas where fiber optic crossover facilities are deployed and those where they are not. Using buffer algorithms, ray casting, and shortest path algorithms, the investment amount and expected return for preset areas where fiber optic crossover facilities are deployed are calculated, thereby determining the transmission network deployment information for those areas. Simultaneously, a planning list is generated to assist operators in making decisions regarding the deployment results.

[0062] In this embodiment, by acquiring B-domain data, O-domain data, and GIS layer data in at least one preset area, and inputting the B-domain data, O-domain data, and GIS layer data into a preset scoring model to obtain a regional score for each area, the transmission network deployment information for the preset area is determined based on the regional score. This allows the transmission network in the preset area to accurately match the user's network needs without relying on personal experience, thus improving the deployment efficiency of the transmission network.

[0063] In some embodiments, the GIS layer data includes user coordinate data and preset area coordinate data; inputting the B-domain data, O-domain data, and GIS layer data into a preset scoring model yields a regional score for each preset area within at least one preset area, including:

[0064] Based on preset classification conditions, labels are created for user coordinate data and preset area coordinate data, resulting in labeled user coordinate data and labeled preset area coordinate data.

[0065] Based on the pre-acquired geographic location information, the tag user coordinate data and the tag preset area coordinate data are calibrated to obtain standard coordinate data;

[0066] The B-domain data, O-domain data, and standard coordinate data are overlaid and merged to obtain the fused data;

[0067] The fused data is input into a preset scoring model to obtain a regional score for each preset region in at least one preset region.

[0068] User coordinate data refers to the coordinates of any user within a preset area. This preset area coordinate data, also known as electronic fence data, includes multiple coordinate points that together form the boundary of the preset area. For example, the preset area coordinate data might include coordinate points A (a, a), B (b, b), C (c, c), and D (d, d). These coordinate points form a rectangle, which represents the extent of the preset area; in other words, this rectangle constitutes the electronic fence of the preset area.

[0069] In the process of calculating regional scores, in order to facilitate the extraction of relevant coordinate data, labels are created for user coordinate data and preset regional coordinate data according to preset classification conditions, resulting in labeled user coordinate data and labeled preset regional coordinate data.

[0070] The preset classification conditions serve as the basis for creating labels. These conditions can be based on industry, income, policy guidance, etc., and will not be elaborated on here.

[0071] Taking income classification as an example, the preset classification conditions can be set as follows: the coordinate data of users with a monthly income of 0 to 10,000 is set as category A1; the coordinate data of users with a total income of 50,000 to 100,000 is set as category A2; the coordinate data of users with a monthly income of 10,000 to 20,000 is set as category B1; the coordinate data of users with a total income of 100,000 to 200,000 is set as category B2; the coordinate data of users with a monthly income of 20,000 to 30,000 is set as category C1; and the coordinate data of users with a total income of 300,000 to 500,000 is set as category C2.

[0072] Let user coordinate data E be E1(e, e), and preset area coordinate data F be F1(f11, f12), F2(f21, f22), F3(f31, f32), and F4(f41, f42). Given that user E's monthly income is 15,000 and the total income of users within preset area F is 350,000, we create a label B1 for user coordinate data E and a label C2 for preset area coordinate data F. This yields categorized user coordinate data and preset area coordinate data, facilitating automated extraction of user coordinate data and preset area coordinate data during the calculation of area scores.

[0073] Geographic location information includes the location relationship between the user and the preset area. The location relationship can be any relationship between objects, such as adjacent relationship or belonging relationship.

[0074] Standard coordinate data includes calibrated tag user coordinate data and tag preset area coordinate data.

[0075] Because the latitude and longitude coordinates of GIS layer data may deviate when displayed on a map, the GIS layer data needs to be calibrated. Therefore, after labeling the user coordinate data and preset area coordinate data in the GIS layer data, the labeled user coordinate data and labeled preset area coordinate data are then calibrated based on pre-acquired geographic location information to obtain standard coordinate data. For example, if user G is known to be located within preset area H, meaning that user G and preset area H have a hierarchical relationship, but the acquired GIS layer data shows user G outside preset area H, then the latitude and longitude offset of user G's coordinate data needs to be adjusted to ensure user G is within preset area H, thus obtaining standard coordinate data.

[0076] After calibrating the GIS layer data of each layer, the B-domain data, O-domain data, and standard coordinate data are overlaid and fused, so that the same preset area contains data with different attributes. In other words, the preset area can simultaneously contain the B-domain data and O-domain data of the preset area, avoiding the situation where the B-domain data and O-domain data are confused with the preset area, and improving the accuracy of the fused data.

[0077] The fused data is input into a preset scoring model to obtain a regional score for each preset region in at least one preset region.

[0078] The fused data accurately includes B-domain and O-domain data within its corresponding preset area. When this fused data is input into the preset scoring model, the resulting regional scores for each preset area are more accurate, reducing the bias caused by manual data processing and improving planning efficiency.

[0079] In some embodiments, at least one preset area includes at least one user; inputting B-domain data, O-domain data, and GIS layer data into a preset scoring model yields a regional score for each preset area within the at least one preset area, including:

[0080] Input the B-domain data, O-domain data, and GIS layer data into the preset scoring model to obtain an individual score for each user among at least one user. The individual score is used to assess the network resource requirements of each user among at least one user.

[0081] Because the B-domain data, O-domain data and GIS layer data are overlaid and merged, the GIS layer data will correspond one-to-one with the B-domain data and O-domain data. In other words, the user's geographical location will correspond one-to-one with the user's B-domain data and O-domain data.

[0082] In some embodiments, at least one user is included in at least one preset area, and an individual score for each user is obtained through a preset scoring model, thereby assessing the user's network resource requirements.

[0083] Based on user coordinate data and preset area coordinate data, determine the target user in each preset area within at least one preset area.

[0084] By performing GIS spatial intersection calculations based on user coordinate data and preset area coordinate data, the positional relationship between the user and the preset area is obtained. When the positional relationship between the user and the preset area is a belonging relationship, the user is identified as the target user of the preset area. The target user within each preset area is determined through the intersection calculation of user coordinate data and preset area coordinate data.

[0085] The individual scores corresponding to the target users in each of the at least one preset region are summed to obtain the regional score for each of the at least one preset region.

[0086] The individual scores of the target users within the preset area are summed to obtain the total score of all individuals in the preset area, which is then used as the regional score for the preset area.

[0087] During the accumulation process, firstly, individuals are categorized based on their scores, and target users are divided into categories A and B, and then categories C and D, in descending order. The formula for calculating the regional score can be expressed as:

[0088] (1)

[0089] Where S represents the regional score. For the nth user in category AB, give an individual rating. This is the individual score for the nth user in category C and D, where Q is the preset regional clustering coefficient. The preset regional clustering coefficient can be set according to needs. For example, if there are 20 users in category C and D in the preset region, the preset regional clustering coefficient is set to 1.2; if there are 40 users in category C and D in the preset region, the preset regional clustering coefficient is set to 1.5.

[0090] In some practical applications, when the users in a preset area include hotels, the hotels are separated when calculating the area score. In this case, users in a preset area can be divided into categories A and B, categories C and D, and hotels. The formula for calculating the area score can be expressed as:

[0091] (2)

[0092] Where S represents the regional score. For the nth user in category AB, give an individual rating. For the nth user in category CD, give an individual rating. Let Q be the individual rating of the nth hotel, and let Q be the preset regional clustering coefficient.

[0093] In some embodiments, determining transmission network deployment information in at least one preset area based on the area score includes: arranging the area scores in descending order to obtain an area score sorting table;

[0094] A higher regional score for a preset area indicates a greater demand for network resources from users within that area. A regional score ranking table is used to determine the priority for deploying fiber optic cabling junction facilities in each preset area, arranged from highest to lowest score.

[0095] Based on the regional scoring and ranking table, determine the transmission network deployment information in at least one preset region.

[0096] Based on the regional scoring and ranking table, at least one preset area is determined for deploying optical cable junction facilities, and optical cable junction boxes are deployed in at least one preset area to carry out transmission network deployment.

[0097] In some embodiments, before inputting B-domain data, O-domain data, and GIS layer data into a preset scoring model to obtain a regional score for each preset region in at least one preset region, the method further includes:

[0098] Obtain sample data, which includes B-domain data, O-domain data, and GIS layer data;

[0099] The weight values ​​corresponding to B-domain data, O-domain data, and GIS layer data are calculated from different dimensions to obtain the preset scoring model.

[0100] Before location scoring, users retrieve a large amount of data from the internal system for statistical analysis, calculating weight values ​​for the data across different dimensions to obtain a pre-defined scoring model. When the relevant data is obtained, the pre-defined scoring model calculates the individual score for the target object based on the correspondence between different data and weight values.

[0101] When scoring based on B-domain data, O-domain data, and GIS layer data, the weights are mainly calculated from dimensions such as user industry, policy guidance, user concentration, and leased line scale. The data is multiplied by its corresponding weight value to obtain a single score. The single scores of different data are added together to obtain the user's individual score.

[0102] To more accurately score users within a preset area, user industries are divided into 8 major categories and 93 subcategories, with different categories corresponding to different scores, so as to avoid the category division being too broad and the user evaluation of specific industries being inaccurate.

[0103] Since the weight values ​​corresponding to the data are calculated from different dimensions, the preset scoring model is a multidimensional scoring model.

[0104] For example, the preset scoring model is the 6D scoring model. The 6D scoring model can calculate the values ​​of six dimensions: the basic score of A and B category enterprises, the basic score of C and D category enterprises, the incremental market competition coefficient, the dedicated line scale coefficient, the policy guidance coefficient, and the preset regional clustering coefficient. Then, the values ​​of these six dimensions are weighted to obtain the individual score of the user.

[0105] In addition, the preset scoring model can also be a 4D model, a 5D model, a 7D model, etc. Different dimensions of scoring models can be selected according to actual needs, and there is no limitation here.

[0106] Figure 2 This is a schematic diagram of a device structure provided in an embodiment of this application. Figure 2 As shown, the device may include an acquisition module 210, an input module 220, and a planning module 230.

[0107] The acquisition module 210 is used to acquire B-domain data, O-domain data and GIS layer data in at least one preset area.

[0108] Input module 220 is used to input B-domain data, O-domain data and GIS layer data into a preset scoring model to obtain a regional score for each preset region in at least one preset region. The regional score is used to evaluate the network resource demand of users in each preset region.

[0109] Planning module 230 is used to determine transmission network deployment information in at least one preset area based on regional scoring.

[0110] In this embodiment, the transmission network to be deployed in the preset area can be accurately matched with the user's network needs without relying on personal experience, thus improving the deployment efficiency of the transmission network.

[0111] In some embodiments, the GIS layer data includes user coordinate data and preset area coordinate data; the input module 220 is specifically used to: establish labels for the user coordinate data and preset area coordinate data according to preset classification conditions, and obtain labeled user coordinate data and labeled preset area coordinate data.

[0112] Based on the pre-acquired geographic location information, the tag user coordinate data and the tag preset area coordinate data are calibrated to obtain standard coordinate data;

[0113] The B-domain data, O-domain data, and standard coordinate data are overlaid and merged to obtain the fused data;

[0114] The fused data is input into a preset scoring model to obtain a regional score for each preset region in at least one preset region.

[0115] In some embodiments, at least one preset area includes at least one user; the input module 220 is specifically used for:

[0116] Input B-domain data, O-domain data and GIS layer data into a preset scoring model to obtain an individual score for each user in at least one user group. The individual score is used to assess the network resource demand of each user in at least one user group.

[0117] Based on user coordinate data and preset area coordinate data, determine the target user in each preset area of ​​at least one preset area;

[0118] The individual scores corresponding to the target users in each of the at least one preset region are summed to obtain the regional score for each of the at least one preset region.

[0119] In some embodiments, the planning module 230 is specifically used to: arrange the regional scores in descending order to obtain a regional score ranking table;

[0120] Based on the regional scoring and ranking table, determine the transmission network deployment information in at least one preset region.

[0121] In some embodiments, before inputting B-domain data, O-domain data and GIS layer data into a preset scoring model to obtain a regional score for each preset region in at least one preset region, the apparatus further includes: a training module for acquiring sample data, the sample data including B-domain data, O-domain data and GIS layer data;

[0122] The weight values ​​corresponding to B-domain data, O-domain data, and GIS layer data are calculated from different dimensions to obtain the preset scoring model.

[0123] Figure 2 Each module in the illustrated device has the ability to implement Figure 1 The functions of each step in the process and their corresponding technical effects are described in detail here for the sake of brevity.

[0124] Figure 3 A schematic diagram of the hardware structure of the transmission network deployment information determination device provided in an embodiment of this application is shown.

[0125] The device for determining information deployment in the transmission network may include a processor 301 and a memory 302 storing computer program instructions.

[0126] Specifically, the processor 301 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0127] Memory 302 may include mass storage for data or instructions. For example, and not limitingly, memory 302 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. In one instance, memory 302 may include removable or non-removable (or fixed) media, or memory 302 may be non-volatile solid-state memory. Memory 302 may be internal or external to the integrated gateway disaster recovery device.

[0128] In one example, memory 302 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, typically, memory 302 includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this application.

[0129] The processor 301 reads and executes computer program instructions stored in the memory 302 to achieve... Figure 1 Steps S110 to S130 in the illustrated embodiment are completed, and the desired outcome is achieved. Figure 1 The technical effects achieved by performing the steps in the example shown are not elaborated here for the sake of brevity.

[0130] In one example, the device for determining network deployment information may further include a communication interface 303 and a bus 310. For example, Figure 3 As shown, the processor 301, memory 302, and communication interface 303 are connected through bus 310 and complete communication with each other.

[0131] The communication interface 303 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0132] Bus 310 includes hardware, software, or both, that couples components of a device together to transmit network deployment information. For example, and not as a limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 310 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0133] The transmission network deployment information determination device can execute the transmission network deployment information determination method in this application embodiment based on B-domain data, O-domain data, and GIS layer data, thereby achieving a combination of... Figure 1 The method described is for determining the deployment information of the transmission network.

[0134] Furthermore, in conjunction with the transmission network deployment information determination method in the above embodiments, this application embodiment can provide a computer-readable storage medium for implementation. This computer-readable storage medium stores computer program instructions; when executed by a processor, these computer program instructions implement any of the transmission network deployment information determination methods in the above embodiments.

[0135] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0136] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0137] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0138] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0139] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for determining network deployment information, characterized in that, include: Acquire B-domain data, O-domain data, and GIS layer data from at least one preset area; The B-domain data, the O-domain data, and the GIS layer data are input into a preset scoring model to obtain a regional score for each preset region in the at least one preset region. The regional score is used to evaluate the network resource demand of users in each preset region. The preset scoring model is a multi-dimensional scoring model, which is used to calculate weight values ​​from multiple dimensions to obtain an individual score for each user. Based on the regional score, determine the transmission network deployment information in the at least one preset region; The GIS layer data includes user coordinate data and preset area coordinate data; the step of inputting the B-domain data, the O-domain data, and the GIS layer data into a preset scoring model to obtain the area score for each preset area in the at least one preset area includes: Based on preset classification conditions, labels are created for the user coordinate data and the preset area coordinate data to obtain labeled user coordinate data and labeled preset area coordinate data. Based on the pre-acquired geographic location information, the tag user coordinate data and the tag preset area coordinate data are calibrated to obtain standard coordinate data; The B-domain data, the O-domain data, and the standard coordinate data are superimposed and fused to obtain fused data; The fused data is input into a preset scoring model to obtain a regional score for each preset region in the at least one preset region.

2. The method according to claim 1, characterized in that, The at least one preset area includes at least one user; the step of inputting the B-domain data, the O-domain data, and the GIS layer data into a preset scoring model to obtain a regional score for each preset area within the at least one preset area includes: The B-domain data, the O-domain data, and the GIS layer data are input into a preset scoring model to obtain an individual score for each of the at least one users. The individual score is used to assess the network resource requirements of each of the at least one users. Based on the user coordinate data and the preset area coordinate data, the target user in each preset area of ​​the at least one preset area is determined; The individual scores corresponding to the target users in each of the at least one preset regions are summed to obtain the regional score for each of the at least one preset regions.

3. The method according to claim 1, characterized in that, The step of determining the transmission network deployment information in the at least one preset area based on the area score includes: The regional scores are arranged in descending order to obtain a regional score ranking table; Based on the regional scoring and sorting table, determine the transmission network deployment information in the at least one preset region.

4. The method according to claim 1, characterized in that, Before inputting the B-domain data, the O-domain data, and the GIS layer data into a preset scoring model to obtain the regional score for each preset region in the at least one preset region, the method further includes: Acquire sample data, which includes B-domain data, O-domain data, and GIS layer data; The weight values ​​corresponding to the B-domain data, O-domain data, and GIS layer data are calculated from different dimensions to obtain the preset scoring model.

5. An apparatus for determining network deployment information, characterized in that, The device includes: The acquisition module is used to acquire B-domain data, O-domain data, and GIS layer data from at least one preset area. The input module is used to input the B-domain data, the O-domain data, and the GIS layer data into a preset scoring model to obtain a regional score for each of the at least one preset regions. The regional score is used to evaluate the network resource demand of users in each preset region. The preset scoring model is a multi-dimensional scoring model used to calculate weight values ​​from multiple dimensions to obtain an individual score for each user. The planning module is used to determine the transmission network deployment information in the at least one preset area based on the area score; The GIS layer data includes user coordinate data and preset area coordinate data; the input module is specifically used for: Based on preset classification conditions, labels are created for the user coordinate data and the preset area coordinate data to obtain labeled user coordinate data and labeled preset area coordinate data. Based on the pre-acquired geographic location information, the tag user coordinate data and the tag preset area coordinate data are calibrated to obtain standard coordinate data; The B-domain data, the O-domain data, and the standard coordinate data are superimposed and fused to obtain fused data; The fused data is input into a preset scoring model to obtain a regional score for each preset region in the at least one preset region.

6. The apparatus according to claim 5, characterized in that, The at least one preset area includes at least one user; the input module is specifically used for: The B-domain data, the O-domain data, and the GIS layer data are input into a preset scoring model to obtain an individual score for each of the at least one users. The individual score is used to assess the network resource requirements of each of the at least one users. Based on the user coordinate data and the preset area coordinate data, the target user in each preset area of ​​the at least one preset area is determined; The individual scores corresponding to the target users in each of the at least one preset regions are summed to obtain the regional score for each of the at least one preset regions.

7. A device for determining network deployment information, characterized in that, The device for determining the transmission network deployment information includes: a processor and a memory storing computer program instructions; The processor reads and executes the computer program instructions to implement the method for determining transmission network deployment information as described in any one of claims 1-4.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions that, when executed by a processor, implement the method for determining transmission network deployment information as described in any one of claims 1-4.

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