Optical splitter deployment scheme determination method and device

Abstract

The invention discloses an optical splitter deployment scheme determination method and device. The method comprises the following steps: acquiring a first installation number of a plurality of sub-regions in a target region at a current timestamp, and analyzing the first installation number of each sub-region by using a first prediction model to obtain a predicted installation number of each sub-region in a first time period; determining a plurality of deployment schemes according to the predicted installation number of each sub-region and the number of pre-deployed optical splitters in the target region; for each deployment scheme, determining the optical splitter resource non-coverage rate of the optical splitter deployed in each sub-region according to the deployment scheme, and analyzing the predicted installation number and the optical splitter resource non-coverage rate of each sub-region by using a second prediction model to obtain the predicted to-be-installed work order number of each sub-region, and based on this, determining a target deployment scheme from a plurality of deployment schemes. The technical problem that a large number of to-be-installed work orders are generated in the target area at the same time due to the fact that an optical splitter in the target area is not deployed in advance in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of data mining technology, and in particular to a method and device for determining a splitter deployment plan. Background Art

[0002] At present, when some families install or relocate broadband, landline, IPTV (Interactive Personal Video Television) and other new services, they may encounter the problem that there are no network resources at the installation address to support the service. In this case, the common solution is: first, the resource configuration personnel initiates a transfer work order; then, after the splitter layout personnel receive the transfer work order, they will go to the installation address to install the splitter to provide splitter resources to the installation address; finally, after the work order is completed (the splitter installation is completed and the address is covered), the resource configuration personnel can connect the user's optical modem to the vacant port of the installed splitter.

[0003] However, due to the connection medium, the standard addresses that a splitter can cover are limited. If enough splitters are built in advance in the region to support the installation needs of any location, this will not only greatly increase the construction cost, but also generate a large number of idle resources. However, if the splitter resources are not deployed in advance, a large number of work orders will be generated. Therefore, how to reasonably deploy splitters in advance to reduce the number of work orders under the premise of limited cost and considering the utilization rate of port resources is an urgent problem to be solved.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present application provide a method and device for determining a splitter deployment plan, so as to at least solve the technical problem that the related art fails to deploy the splitters in the target area in advance, resulting in a large number of work orders to be transferred to be installed in the target area at the same time.

[0006] According to one aspect of an embodiment of the present application, a method for determining a splitter deployment plan is provided, comprising: obtaining a first installed quantity of network communication equipment installed in multiple sub-areas in a target area within a current timestamp, and using a pre-trained first prediction model to analyze the first installed quantity of each sub-area within the current timestamp to obtain a predicted installed quantity corresponding to each sub-area within a first time period, wherein the first time period is any time period after the current timestamp; determining multiple initial deployment plans based on the predicted installed quantity corresponding to each sub-area within the first time period and a first quantity of pre-deployed splitters in the target area; for each initial deployment plan, determining a splitter resource non-coverage rate when each sub-area deploys splitters according to the initial deployment plan, and using The predicted number of installations and the non-coverage rate of the splitter resources of each sub-area in the first time period are analyzed by using a pre-trained second prediction model to obtain the predicted number of work orders to be installed corresponding to each sub-area when the splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of the splitter resources is a first ratio of a second number of standard addresses that are still not covered by the splitter after the sub-area pre-deploys the splitter according to the initial deployment plan to a third number of standard addresses that are not covered by the operator's business in the sub-area in the current timestamp; determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted numbers of work orders to be installed of all sub-areas in the target area in the first time period less than a first threshold.

[0007] Optionally, the training process of the first prediction model includes: obtaining multiple groups of first sample data, wherein the first sample data includes: a second installed quantity of a target sub-region within the target area within a past timestamp and a third installed quantity of the target sub-region within a second time period, and the second time period is any time period after the past timestamp, and the target sub-region is any sub-region among multiple sub-regions within the target area; constructing a first neural network model, wherein the first neural network model includes at least: a coding layer, an input layer, a hidden layer, and an output layer; and iteratively training the first neural network model using multiple groups of first sample data to obtain a first prediction model.

[0008] Optionally, the first number of pre-deployed splitters in the target area satisfies the following conditions: the first number does not exceed a preset number; a second ratio of the sum of the total number of ports of the first number of splitters and the total number of vacant ports of the splitters deployed in the target area within the current timestamp divided by the total number of ports of the splitters deployed in the target area within the current timestamp does not exceed a preset port vacancy rate.

[0009] Optionally, multiple initial deployment plans are determined based on the predicted installed capacity of each sub-area in the future time period and the first number of pre-deployed splitters in the target area, including: for each sub-area, determining a third ratio of the predicted installed capacity of the sub-area in the first time period to a third number of standard addresses of the sub-area that are not covered by the operator's business in the current timestamp; determining whether the third ratio is less than a preset second threshold, and determining whether a fourth number of splitters to be deployed in the sub-area is zero based on the comparison result; and deploying the first number of splitters in at least one sub-area based on whether the fourth number of splitters to be deployed in each sub-area is zero, thereby obtaining multiple initial deployment plans.

[0010] Optionally, determining the non-coverage rate of splitter resources when each sub-area deploys splitters according to the initial deployment plan includes: determining a fourth number of splitters deployed in each sub-area defined in the initial deployment plan and a fifth number of standard addresses covered by each splitter; for each sub-area, determining a sixth number of standard addresses not covered by the splitter in the sub-area at a current timestamp, determining the product of the fourth number and the fifth number, and taking the difference between the sixth number and the obtained product as a second number; determining a second ratio of the second number to a third number of standard addresses for operator services not covered in the sub-area at a current timestamp; and taking the second ratio as the non-coverage rate of splitter resources when the sub-area deploys the splitters according to the initial deployment plan.

[0011] Optionally, the training process of the second prediction model includes: obtaining multiple groups of second sample data, wherein the second sample data include: the number of installations and the non-coverage rate of spectrometer resources in the target sub-area within the target area in the past timestamp and the number of transferred work orders for installation in the target sub-area within the second time period, and the target sub-area is any sub-area among the multiple sub-areas in the target area, and the second time period is any time period after the past timestamp; constructing a second neural network model, wherein the second neural network model includes at least: a coding layer, an input layer, a hidden layer, and an output layer; using multiple groups of second sample data to iteratively train the second neural network model to obtain a second prediction model.

[0012] Optionally, before using the pre-trained second prediction model to analyze the predicted installed capacity and spectrometer resource coverage rate of each sub-area in the first time period, the method also includes: determining the average and standard deviation of the installed capacity of all sub-areas in the target area in the first time period; and using the average and standard deviation to standardize the predicted installed capacity of each sub-area in the first time period.

[0013] According to another aspect of an embodiment of the present application, a method for determining a splitter deployment plan is also provided, including: obtaining a first installed quantity of network communication equipment installed in multiple sub-areas in a target area within a current timestamp, and determining a predicted installed quantity corresponding to each sub-area in a first time period according to the first installed quantity of each sub-area in the current timestamp; determining multiple initial deployment plans according to the predicted installed quantity corresponding to each sub-area in the first time period and a first quantity of pre-deployed splitters in the target area; for each initial deployment plan, determining a splitter resource non-coverage rate when each sub-area deploys splitters according to the initial deployment plan, and determining a predicted installed quantity corresponding to each sub-area in the first time period according to the predicted installed quantity corresponding to each sub-area in the first time period The predicted number of installed devices and the non-coverage rate of splitter resources in the segment determine the predicted number of work orders to be transferred to installation corresponding to each sub-area when the splitter is deployed according to the initial deployment plan within the first time period, wherein the non-coverage rate of splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area within the current timestamp; determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted numbers of work orders to be transferred to installation for all sub-areas in the target area within the first time period less than a first threshold.

[0014] According to another aspect of an embodiment of the present application, a device for determining a splitter deployment plan is also provided, including: a first prediction module, used to obtain a first installed quantity of network communication equipment installed in multiple sub-areas in a target area within a current timestamp, and use a pre-trained first prediction model to analyze the first installed quantity of each sub-area within the current timestamp to obtain the predicted installed quantity corresponding to each sub-area within a first time period, wherein the first time period is any time period after the current timestamp; a first determination module, used to determine multiple initial deployment plans based on the predicted installed quantity corresponding to each sub-area within the first time period and the first quantity of pre-deployed splitters in the target area; a second prediction module, used to determine, for each initial deployment plan, the number of splitters in each sub-area when the splitters are deployed according to the initial deployment plan The pre-trained second prediction model is used to analyze the predicted installed quantity and the non-coverage rate of the splitter resources of each sub-area in the first time period, and obtain the predicted number of work orders to be installed corresponding to each sub-area when the splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of the splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area in the current timestamp; a second determination module is used to determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted numbers of work orders to be installed of all sub-areas in the target area in the first time period less than a first threshold.

[0015] According to another aspect of an embodiment of the present application, a device for determining a splitter deployment plan is also provided, including: a third prediction module, used to obtain a first installed quantity of network communication equipment installed in multiple sub-areas in a target area within a current timestamp, and determine the predicted installed quantity corresponding to each sub-area in a first time period according to the first installed quantity of each sub-area in the current timestamp; a third determination module, used to determine multiple initial deployment plans according to the predicted installed quantity corresponding to each sub-area in the first time period and the first quantity of pre-deployed splitters in the target area; a fourth prediction module, used to determine, for each initial deployment plan, the non-coverage rate of splitter resources when each sub-area deploys splitters according to the initial deployment plan, and determine the non-coverage rate of splitter resources according to each sub-area according to the first installed quantity The predicted number of installed devices in each sub-area in the first time period and the non-coverage rate of splitter resources determine the predicted number of work orders to be installed when each sub-area deploys the splitter according to the initial deployment plan in the first time period, wherein the non-coverage rate of splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area in the current timestamp; a fourth determination module is used to determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted numbers of work orders to be installed of all sub-areas in the target area in the first time period less than a first threshold.

[0016] According to another aspect of an embodiment of the present application, a computer program product is further provided. The computer program product includes a stored computer program, wherein when the computer program is executed by a processor, the above-mentioned method for determining a splitter deployment scheme is implemented.

[0017] According to another aspect of an embodiment of the present application, an electronic device is further provided, the electronic device comprising: a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to execute the above-mentioned method for determining a splitter deployment scheme through the computer program.

[0018] In an embodiment of the present application, first, a first prediction model is used to analyze the first installed capacity of each sub-area in the target area within the current timestamp to obtain the predicted installed capacity of each sub-area in the target area in the future period; then, under the premise of a certain number of spectrometers, multiple initial deployment plans are designed according to the predicted installed capacity of each sub-area in the target area in the future period; then, the non-coverage rate of the spectrometer resources of each sub-area when the spectrometers are deployed according to each spectrometer deployment plan is calculated, and the predicted installed capacity and the non-coverage rate of the spectrometer resources of each sub-area in the first time period are analyzed by using a second prediction model. The predicted number of work orders to be transferred to installation in each sub-area when the optical splitter is deployed according to the initial deployment plan in a future period of time is obtained; finally, a target deployment plan is determined from multiple initial deployment plans so that the sum of the predicted number of work orders to be transferred to installation in each sub-area in the first time period is less than a first threshold, so that when the optical splitter is deployed according to the target deployment plan, the number of work orders to be transferred to installation in a future period of time can be minimized, and the risk of user complaints due to long waiting time is reduced, thereby solving the technical problem that the relevant technology does not deploy the optical splitter in the target area in advance, resulting in a large number of work orders to be transferred to installation in the target area at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0020] Figure 1 It is a hardware structure block diagram of a computer terminal (or mobile device) for implementing a method for determining a splitter deployment scheme according to an embodiment of the present application;

[0021] Figure 2 is a flow chart of an optional method for determining a splitter deployment scheme according to an embodiment of the present application;

[0022] Figure 3 is a flow chart of another optional method for determining a splitter deployment scheme according to an embodiment of the present application;

[0023] Figure 4 is a schematic structural diagram of an optional device for determining a splitter deployment scheme according to an embodiment of the present application;

[0024] Figure 5 is a structural schematic diagram of another optional device for determining a splitter deployment scheme according to an embodiment of the present application;

[0025] Figure 6 It is a schematic diagram of the structure of another optional electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] In addition, the relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. For example, an interface is set up between this system and the relevant user or organization. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0029] In order to better understand the embodiments of the present application, the technical terms involved in the embodiments of the present application are explained as follows:

[0030] Optical Splitter: A passive device used to split and combine light wave energy, that is, it has the function of distributing downstream data and concentrating upstream data. Generally, an optical splitter has one upstream port and multiple downstream ports, and each downstream port can be connected to a household optical modem.

[0031] Transfer to installation work order: refers to the initiation of installation business at the user's standard address (i.e. the user's installation address) but at an address not covered by splitter resources. The resource configuration personnel must first initiate a transfer to installation work order. After receiving the transfer to installation work order, the splitter layout personnel go to the corresponding installation address to install the splitter. After that, the transfer to installation work order is completed. At this time, the splitter is installed and covers the installation address. Only then can the subsequent resource configuration personnel connect the user's optical modem to the vacant port of the covered splitter.

[0032] Example 1

[0033] In the related art, when some users are handling new installation or relocation services for broadband, fixed-line, and IPTV, they will encounter the problem that the installation address (i.e., the address where the user initiates the new installation or relocation service) is not covered by the splitter resources. In this case, the common solution is: first, the resource configuration personnel initiate a transfer work order; then, after the splitter layout personnel receive the transfer work order, they will go to the installation address to install the splitter to provide the splitter resources to the installation address; finally, after the work order is completed (the splitter installation is completed and the address is covered), the resource configuration personnel can connect the user's optical modem to the vacant port of the installed splitter. However, this method of constructing splitter resources after the user submits the service application will greatly increase the user's service application waiting time, resulting in reduced user satisfaction and even complaints.

[0034] In order to solve this problem, a relevant solution is provided in the embodiments of the present application, which is described in detail below.

[0035] According to an embodiment of the present application, a method embodiment of a method for determining a splitter deployment scheme is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0036] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 The hardware structure block diagram of a computer terminal (or mobile device) for implementing the method for determining the optical splitter deployment scheme is shown. Figure 1As shown, the computer terminal 10 (or mobile device 10) may include one or more (102a, 102b, ..., 102n are used to illustrate) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0037] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0038] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the method for determining the deployment scheme of the optical splitter in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, the method for determining the deployment scheme of the optical splitter of the above-mentioned application is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0039] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0040] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or mobile device).

[0041] In the above operating environment, Figure 2 is a flow chart of an optional method for determining a splitter deployment scheme according to an embodiment of the present application, such as Figure 2 As shown, the method at least includes steps S202-S208, wherein:

[0042] Step S202, obtain the first installed quantity of network communication equipment installed in multiple sub-areas in the target area within the current timestamp, and use the pre-trained first prediction model to analyze the first installed quantity of each sub-area within the current timestamp to obtain the predicted installed quantity corresponding to each sub-area in the first time period.

[0043] In the technical solution provided in step S202, the multiple sub-areas in the above-mentioned target area can be understood as dividing the target area into multiple grids of equal size and non-overlapping, and each grid represents a sub-area. The installation of network communication equipment (also known as installation service) can be understood as the user's application for new installation or relocation services for broadband, fixed-line, and IPTV. Since the number of installations in different areas in different timestamps is different, and the number of installations corresponding to each sub-area at the same timestamp in previous years is roughly the same, the embodiment of the present application can use the number of installations in each sub-area at different timestamps in previous years to train a first prediction model, and use the pre-trained first prediction model to analyze the first installed number of each sub-area in the current timestamp, and obtain the predicted installed number corresponding to each sub-area in the first time period (any time period after the current timestamp).

[0044] Step S204 , determining a plurality of initial deployment schemes according to the predicted installed capacity corresponding to each sub-area in the first time period and the first quantity of pre-deployed optical splitters in the target area.

[0045] In the technical solution provided in step S204, a plurality of initial deployment plans are first formulated according to the first number of optical splitters to be deployed in the target area and the predicted number of installations corresponding to each sub-area in the first time period, wherein the sum of the number of optical splitters installed in all sub-areas is defined in each initial deployment plan to be equal to the first number, and the number of optical splitters installed in each sub-area is greater than or equal to 0 and less than the first number.

[0046] Step S206, for each initial deployment plan, determine the non-coverage rate of spectrometer resources in each sub-area when the spectrometer is deployed according to the initial deployment plan, and use the pre-trained second prediction model to analyze the predicted installed quantity and the non-coverage rate of spectrometer resources in each sub-area in the first time period, and obtain the predicted number of work orders to be installed corresponding to each sub-area when the spectrometer is deployed according to the initial deployment plan in the first time period.

[0047] In the technical solution provided in step S206, each initial deployment plan is analyzed to determine the non-coverage rate of the splitter resources when each sub-area deploys the splitter according to the initial deployment plan, wherein the non-coverage rate of the splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses of the operator's service that are not covered by the sub-area in the current timestamp. Then, the predicted number of installations and the non-coverage rate of the splitter resources of each sub-area in the first time period are analyzed using the second prediction model to obtain the predicted number of work orders to be installed corresponding to each sub-area when the splitter is deployed according to the initial deployment plan in the first time period.

[0048] Step S208: determining a target deployment plan for each sub-area in the first time period from among the multiple initial deployment plans.

[0049] In the technical solution provided in step S208, a target deployment solution is determined from multiple initial deployment solutions, which makes the sum of the predicted number of work orders to be installed in all sub-areas in the target area within the first time period less than a first threshold. Finally, a first number of splitters are deployed in the target area according to the target deployment solution, ensuring that all user services in the target area can be processed in a timely manner, thereby improving user satisfaction.

[0050] The above method of this embodiment is further introduced below.

[0051] As an optional implementation, in the technical solution provided in the above step S202, the first prediction model is also called an installation quantity (Installation Quantity, IQ) prediction model, and its training process may include:

[0052] Step 1: Obtain multiple groups of first sample data.

[0053] Specifically, the above-mentioned first sample data includes: the second installed quantity of the target sub-area within the target area in the past timestamp and the third installed quantity of the target sub-area within the second time period, wherein the target sub-area is any sub-area among multiple sub-areas within the target area, and the second time period is any time period after the past timestamp.

[0054] For example, the first sample data may be: the second installed capacity of sub-region 1 (1 is the sub-region number) in the target area on September 11, 2023 (i.e., a past timestamp) is 10, and the third installed capacity of sub-region 1 on September 12, 2023 (i.e., a second time period) is 5. Alternatively, the first sample data may be: the second installed capacity of sub-region 6 (6 is the sub-region number) in the target area on November 13, 2022 (i.e., a past timestamp) is 5, and the third installed capacity of sub-region 6 on November 14, 2022 (i.e., a second time period) is 15.

[0055] Step 2: Build the first neural network model.

[0056] Specifically, the first neural network model at least includes: a coding layer, an input layer, a hidden layer (multiple layers in total), and an output layer. The coding layer encodes the input information (i.e., the second number of installed units in the target sub-region in the past timestamp), the hidden layer processes and extracts features from the coded information, and the output layer generates the final predicted number of installed units based on the output of the hidden layer.

[0057] Step 3: Use multiple groups of first sample data to iteratively train the first neural network model to obtain a first prediction model.

[0058] Specifically, for each group of first sample data, the second installed capacity of the sub-region within the first sample data in the past timestamp is input into the first neural network model, and analyzed by the first neural network model to output the predicted installed capacity of the sub-region in the second time period; a first loss function is constructed based on the predicted installed capacity of the sub-region in the second time period and the third installed capacity of the sub-region in the first sample data in the second time period; model parameters of the first neural network model are adjusted based on the first loss function until the model converges, and finally the first prediction model is obtained.

[0059] Furthermore, in the technical solution provided in the above step S202, the embodiment of the present application can use the above-mentioned trained first prediction model to perform the following analysis on the first installed quantity of each sub-area in the current timestamp to obtain the predicted installed quantity corresponding to each sub-area in the first time period.

[0060] For each sub-region, the number of installed units at different timestamps is different. Therefore, the coding layer can be used to number the sub-regions g i For geographic location coding, the one-hot algorithm is used in the embodiment of the present application to number the sub-region g. i Encode it and map it into binary code to represent the vector V with dimension G gi ∈R G , where G is the total number of all sub-regions in the target region. For example, the sub-region numbered 5 (G=10) can be mapped to the binary code 0000100000 through one-hot encoding. As for the time information encoding, in the embodiment of the present application, the features of the timestamp t can be extracted and spliced ​​into a vector V with a dimension of 26 t ∈R 26 , where the extracted time features are encoded by the one-hot algorithm, including the months of the year, weeks of the month, days of the week, and whether it is a holiday. For example, March 12, 2024 is the third month of the year, the third week of March, the second day of the week, and it is not a holiday. Therefore, the time information can be converted into vectors [0,0,1,0,0,0,0,0,0,0,0,0], [0,0,1,0,0,0], [0,1,0,0,0,0,0] and [0], and these vectors are concatenated to encode the time information.

[0061] Then, the time vector V output by the encoding layer is t and position vector V gi splicing, as the input of the hidden layer, and the output layer outputs the first number of installed units in the sub-region within a period of time T in the future, recorded as

[0062] For example, the target area A is divided into 6 sub-areas, each of which is numbered g. i , and March 12, 2024 is taken as the current timestamp t. For sub-region g1, its geographic location information and time information are encoded and concatenated to obtain the input vector [1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0], which is input into the first prediction model to obtain the predicted installed capacity of sub-region g1 in the first time period in the future as 20. In this way, the installed capacity of the other five sub-regions g2, g3, g4, g5, and g6 in the first time period in the future is calculated to be 100, 7, 35, 170, and 8 respectively.

[0063] It should be noted that in the above step S202, the first prediction model can be loaded into the memory, for example, the raw data of the first prediction model can be loaded from the non-volatile memory into the volatile memory, so that the processor runs the first prediction model. The raw data of the first prediction model refers to unprocessed data, which usually includes parameters and structural data of the first prediction model. The structural data can be a calculation relationship based on the parameters, such as the forward propagation calculation relationship between the intermediate layers and the neurons. Specifically, the structural data can include the code related to the structure of the first prediction model, such as the code for performing related calculations between the intermediate layers and the neurons.

[0064] In one embodiment, an area for loading the first prediction model can be divided in the memory, which can include a structure data storage area and a parameter storage area. The structure data storage area is used to store structure-related codes, and the parameters referenced by it can point to the address of a specific parameter in the parameter storage area through a pointer. During the training process of the first prediction model, it may be necessary to frequently update the parameters, and the parameter values ​​in the parameter storage area can be updated.

[0065] As an optional implementation, in the technical solution provided in the above step S204, the first number N of pre-deployed optical splitters in the target area satisfies the following conditions:

[0066] First: funding constraints.

[0067] The first quantity does not exceed a preset quantity, where the preset quantity is a maximum quantity N′ that can be purchased within the scope of the procurement funds, that is, N≤N′.

[0068] Second: port vacancy rate limit.

[0069] A second ratio of the sum of the total number of ports of the first number of optical splitters and the total number of vacant ports of the optical splitters deployed in the target area within the current timestamp divided by the total number of ports of the optical splitters deployed in the target area within the current timestamp does not exceed a preset port vacancy rate, that is:

[0070]

[0071] Wherein, c is the number of ports of the optical splitter, so N*c represents the total number of ports of the first number of optical splitters;

[0072] Represents sub-region g i The number of vacant ports of the optical splitter at timestamp t, G represents the number of sub-areas in the target area, so Indicates the total number of vacant ports of the optical splitter deployed in the target area within the current timestamp; Represents sub-region g iThe number of ports on the splitter at timestamp t, Indicates the total number of ports of the optical splitter deployed in the target area within the current timestamp; Indicates the preset port vacancy rate, which can be set according to the actual application scenario.

[0073] As an optional implementation, in the technical solution provided in the above step S204, the method may include:

[0074] Step S2041: for each sub-area, determine a third ratio of the predicted number of installed devices in the sub-area in the first time period to a third number of standard addresses of the sub-area that are not covered by the operator's service in the current timestamp.

[0075] The third number of standard addresses of the operator's services that are not covered by the above sub-area within the current timestamp can be recorded as Therefore, the third ratio can be written as:

[0076] Step S2042: determine whether the third ratio is less than a preset second threshold, and determine whether a fourth number of optical splitters to be deployed in the sub-area is zero according to the comparison result.

[0077] The second threshold can be set according to the actual application scenario. The fourth number of optical splitters to be deployed in the sub-area can be denoted as r gi ,and Therefore, the above step S2042 can be understood as: In the case of i The fourth number r of optical splitters to be deployed in gi =0; otherwise, In the case of i The fourth number r of optical splitters to be deployed in gi ≠0.

[0078] Step S2043: Deploy the first number of optical splitters in at least one sub-area according to whether the fourth number of optical splitters to be deployed in each sub-area is zero, thereby obtaining a plurality of initial deployment schemes.

[0079] That is, according to whether the number of optical splitters to be deployed in each sub-area is zero, the first number of optical splitters is deployed in at least one sub-area in a permutation and combination manner to obtain multiple initial deployment plans. The purpose of this is that the deployment plan that tends to deploy optical splitters in sub-areas where the predicted number of installed devices is far less than the number of service uncovered addresses will produce weaker benefits. Therefore, when determining the initial deployment plan, optical splitters will no longer be deployed in such sub-areas, thereby optimizing deployment efficiency with minimal performance loss.

[0080] For example, according to the construction cost budget and the splitter port vacancy rate limit, the total number of splitters to be deployed in the six sub-areas g1, g2, g3, g4, g5, and g6 in the target area A in the first time period in the future (such as one month) is 3 (i.e., N=3). In addition, the respective third ratios are determined by the predicted installed capacity of the above six sub-areas g1, g2, g3, g4, g5, and g6 and the third number of standard addresses of the operator's business that are not covered in each sub-area at the current timestamp t.

[0081] Assume α = 0.05, and Therefore, the number of splitters deployed in sub-areas g1, g3, and g6 is 0. Therefore, for the above 6 grids, there are 10 initial deployment schemes as follows: (0,0,0,1,2,0), (0,0,0,2,1,0), (0,0,0,0,3,0), (0,0,0,3,0,0), (0,1,0,1,1,0), (0,1,0,0,2,0), (0,1,0,2,0,0), (0,2,0,1,0,0), (0,3,0,0,0,0). Among them, the (0,0,0,1,2,0) scheme means that 0 splitters are deployed in g1, g2, g3, and g6, one splitter is deployed in g4, and two splitters are deployed in g5.

[0082] As an optional implementation, in the technical solution provided in the above step S206, the process of determining the non-coverage rate of the optical splitter resources may include:

[0083] First, a fourth number of optical splitters deployed in each sub-area defined in the initial deployment plan and a fifth number of standard addresses covered by each optical splitter are determined.

[0084] Then, for each sub-area, determine the sixth number of standard addresses that are not covered by the splitter in the sub-area within the current timestamp, determine the product of the fourth number and the fifth number, and use the difference between the sixth number and the obtained product as the second number; determine a second ratio of the second number to the third number of standard addresses for operator services that are not covered in the sub-area within the current timestamp; and use the second ratio as the splitter resource coverage rate when the sub-area deploys the splitter according to the initial deployment plan.

[0085] In this embodiment, the fourth quantity can be recorded as r gi , the fifth number of standard addresses that each optical splitter can cover can be recorded as b, so the product of the fourth number and the fifth number is r gi *b can be understood as: sub-area g i Deploy r in the first period of time in the future giThe total number of standard addresses that can be covered by the optical splitter. The sixth number is recorded as Therefore, the difference between the sixth quantity and the product of the fourth quantity and the fifth quantity, that is, the second quantity, can be expressed as: The sub-region g i The third number of standard addresses that are not covered by the operator's service at the current timestamp can be recorded as Therefore, the sub-region g i The ratio of optical splitter resources not covered when the optical splitter is deployed according to the initial deployment plan It can be expressed as:

[0086]

[0087] For example, for the six sub-areas g1, g2, g3, g4, g5, and g6 in the target area A, the original splitter resource coverage rate is They are: After obtaining multiple initial deployment schemes through step S204, each initial scheme can be used to update the non-coverage rate of the optical splitter resources. For example, scheme 1 (0, 0, 0, 1, 2, 0) only needs to update the non-coverage rate of the optical splitter resources of the sub-areas, so that the non-coverage rate of the optical splitter resources of the six sub-areas g1, g2, g3, g4, g5, and g6 in the target area A is They are Here, 32 is the fifth number of standard addresses that can be covered by a single optical splitter.

[0088] Further, as an optional implementation, in the technical solution provided in the above step S206, the training process of the second prediction model includes:

[0089] Step 1: Obtain multiple sets of second sample data.

[0090] The second sample data includes: the number of installations and the non-coverage rate of optical splitter resources in the target sub-area within the target area in the past timestamp, and the number of transferred work orders for installation in the target sub-area in the past time period.

[0091] Step 2: Build the second neural network model.

[0092] Specifically, the second neural network model at least includes: a coding layer, an input layer, a hidden layer (multiple layers in total), and an output layer. The coding layer encodes the input information (the number of installations in the target sub-area in the past timestamp and the non-coverage rate of the spectrometer resources), the hidden layer processes and extracts features from the coded information, and the output layer generates the final predicted number of work orders to be installed based on the output of the hidden layer.

[0093] Step 3: Use multiple sets of second sample data to iteratively train the second neural network model to obtain a second prediction model.

[0094] Specifically, for each group of second sample data, the number of installations and the non-coverage rate of spectrometer resources in the target sub-area in the second sample data in the past time period are input into the second neural network model, and analyzed by the second neural network model to output the predicted number of work orders to be transferred to installation in the target sub-area in the second time period; a second loss function is constructed based on the predicted number of work orders to be transferred to installation in the sub-area in the second time period and the number of work orders to be transferred to installation in the target sub-area in the second sample data in the second time period; the model parameters of the second neural network model are adjusted based on the second loss function until the model converges, and finally the second prediction model is obtained.

[0095] It should be noted that in the above step S206, the second prediction model can be loaded into the memory, for example, the raw data of the second prediction model can be loaded from the non-volatile memory into the volatile memory, so that the processor runs the second prediction model. The raw data of the second prediction model refers to unprocessed data, usually including parameters and structural data of the second prediction model. The structural data can be a calculation relationship based on the parameters, such as the forward propagation calculation relationship between the intermediate layers and the neurons. Specifically, the structural data can include the code related to the structure of the second prediction model, such as the code for performing related calculations between the intermediate layers and the neurons.

[0096] In one embodiment, an area for loading the second prediction model can be divided in the memory, which can include a structure data storage area and a parameter storage area. The structure data storage area is used to store structure-related codes, and the parameters referenced by it can point to the address of a specific parameter in the parameter storage area through a pointer. During the training process of the second prediction model, it may be necessary to frequently update the parameters, and the parameter values ​​in the parameter storage area can be updated.

[0097] For example, for the target sub-area g1 in the target area A, its geographical location information, time information, standardized installed capacity and the non-coverage rate of the splitter resources are encoded and spliced ​​to obtain the input vector And input it into the second prediction model to obtain the predicted number of work orders to be transferred to waiting for installation in the target sub-area g1 in the first time period in the future, which is 2. In this way, the number of installations in the other five sub-areas g2, g3, g4, g5, and g6 in the first time period in the future is calculated to be 3, 0, 2, 9, and 2 respectively. Therefore, the total number of work orders to be transferred to waiting for installation in the target area A is 18.

[0098] Furthermore, after obtaining the above-mentioned second prediction model, the second prediction model can be used to analyze the predicted installed capacity and the non-coverage rate of the optical splitter resources in each sub-area in the first time period. Prior to this, since the non-coverage rate of the optical splitter resources is an input feature, its value range is between 0 and 1, so there is no need to process it; and the predicted installed capacity is a value greater than or equal to 1. In order to ensure the uniformity of the input data, the predicted installed capacity can be standardized according to the following method:

[0099] Step 1: Determine the mean and standard deviation of the predicted installed capacity in the first time period for all sub-regions in the target region;

[0100] Step 2: Use the mean and standard deviation values ​​to standardize the predicted installed capacity of each sub-region in the first time period according to the following formula:

[0101]

[0102] in, represents the sub-region g before normalization i The predicted number of installed capacity in the first time period, represents the normalized sub-region g i The forecasted number of installed capacity in the first time period.

[0103] Through the technical solution provided in the above step S206, the predicted number of work orders to be transferred to installation corresponding to each sub-area in the target area when the optical splitter is deployed according to each initial deployment plan in the first time period can be obtained, that is, the total number of work orders to be transferred to installation in the whole area under each initial deployment plan. In order to minimize the number of work orders to be transferred to installation and reduce the average installation waiting time of users, a target deployment plan can be selected from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted number of work orders to be transferred to installation in all sub-areas in the target area in the first time period less than the first threshold.

[0104] For example, if the six sub-areas g1, g2, g3, g4, g5, and g6 in the target area A are deployed with splitters according to the above 10 initial deployment plans, the minimum total number of work orders to be transferred to be installed is 11, and the corresponding allocation plan is (0, 0, 0, 1, 2, 0). Therefore, under the premise that the first number of splitters to be deployed is limited to 3, two splitters are deployed in the g4 sub-area and one splitter is deployed in the g5 sub-area, which can minimize the number of work orders to be transferred to be installed in the first time period in the future, thereby reducing the average installation waiting time of users and reducing the risk of user complaints.

[0105] Based on the scheme defined in the above steps S202 to S208, it can be known that in the embodiment, considering the construction cost and resource utilization, it is impossible to construct the splitter resources for all standard addresses in the target area in advance to reduce the number of resource transfer work orders. The embodiment of the present application proposes: first, using the first prediction model to analyze the first installed quantity of each sub-area in the target area within the current timestamp to obtain the predicted installed quantity of each sub-area in the target area in the future; then, under the premise of a certain number of splitters, design a plurality of initial deployment schemes according to the predicted installed quantity of each sub-area in the target area in the future; then, calculate the non-coverage rate of the splitter resources for each sub-area when the splitter is deployed according to each splitter deployment scheme , and use the second prediction model to analyze the predicted installed quantity and the non-coverage rate of splitter resources in each sub-area in the first time period, and obtain the predicted number of work orders to be transferred to waiting for installation when each sub-area deploys the splitter according to the initial deployment plan in the future period; finally, determine the target deployment plan from multiple initial deployment plans so that the sum of the predicted number of work orders to be transferred to waiting for installation in each sub-area in the first time period is less than the first threshold, so that when the splitter is deployed according to the target deployment plan, the number of work orders to be transferred to waiting for installation in the future period can be minimized, and the risk of user complaints due to long waiting time is reduced, thereby solving the technical problem that the relevant technology does not deploy the splitter in the target area in advance, resulting in a large number of work orders to be transferred to waiting for installation in the target area at the same time.

[0106] Example 2

[0107] In the above Figure 1 In the operating environment shown, the embodiment of the present application also provides another method for determining a splitter deployment solution. Figure 3 is a flow chart of an optional method for determining a splitter deployment scheme according to an embodiment of the present application, such as Figure 3 As shown, the method at least includes steps S302-S308, wherein:

[0108] Step S302, obtaining the first installed quantity of network communication equipment installed in multiple sub-areas in the target area within the current timestamp, and determining the predicted installed quantity corresponding to each sub-area in the first time period according to the first installed quantity of each sub-area within the current timestamp.

[0109] In the technical solution provided in step S302, the specific implementation method of determining the predicted installed capacity corresponding to each sub-area in the first time period based on the first installed capacity of each sub-area in the current timestamp can refer to the technical solution provided in the above step S202. The embodiment of the present application does not impose specific restrictions on the specific implementation method.

[0110] Step S304 , determining a plurality of initial deployment schemes according to the predicted installed capacity corresponding to each sub-area in the first time period and the first quantity of pre-deployed optical splitters in the target area.

[0111] The implementation process of the technical solution provided in step S304 may refer to the technical solution provided in the above step S302.

[0112] Step S306, for each initial deployment plan, determine the non-coverage rate of splitter resources when each sub-area deploys the splitter according to the initial deployment plan, and determine the corresponding predicted number of work orders to be transferred to be installed when each sub-area deploys the splitter according to the initial deployment plan in the first time period based on the predicted installed quantity and the non-coverage rate of splitter resources in each sub-area in the first time period.

[0113] In the technical solution provided in step S306, the specific implementation method of determining the predicted number of work orders to be installed corresponding to each sub-area when the spectrometer is deployed according to the initial deployment plan within the first time period based on the predicted installed quantity of each sub-area within the first time period and the non-coverage rate of the spectrometer resources can refer to the technical solution provided in the above step S206. The embodiment of the present application does not impose any specific restrictions on the specific implementation method.

[0114] Step S308: determining a target deployment plan for each sub-area in the first time period from among the multiple initial deployment plans.

[0115] In the technical solution provided in step S308, the target deployment solution is a deployment solution that makes the sum of the number of work orders to be transferred to be installed in all sub-areas in the target area predicted within the first time period less than a first threshold.

[0116] It should be noted that the technical solutions provided by the above steps S302-S308 are similar to the technical solutions provided by steps S202-S208 in some places, so the specific implementation methods of steps S302-S308 are not elaborated in detail in the embodiment of the present application.

[0117] Based on the scheme defined in the above steps S302 to S308, it can be known that in the embodiment, considering the construction cost and resource utilization, it is impossible to construct the splitter resources for all standard addresses in the target area in advance to reduce the number of resource transfer work orders. The embodiment of the present application proposes: first, the first installed quantity of each sub-area in the target area within the current timestamp is analyzed to obtain the predicted installed quantity of each sub-area in the target area in the future; then, under the premise of a certain number of splitters, a plurality of initial deployment schemes are designed according to the predicted installed quantity of each sub-area in the target area in the future; then, the non-coverage rate of the splitter resources is calculated for each sub-area when the splitter is deployed according to each splitter deployment scheme , and analyze the predicted number of installations and the non-coverage rate of splitter resources in each sub-area in the first time period, and obtain the predicted number of work orders to be transferred to waiting for installation when each sub-area deploys splitters according to the initial deployment plan in the future period; finally, determine a target deployment plan from multiple initial deployment plans that makes the sum of the predicted number of work orders to be transferred to waiting for installation in each sub-area in the first time period less than a first threshold, so that when the splitter is deployed according to the target deployment plan, the number of work orders to be transferred to waiting for installation in the future period can be minimized, and the risk of user complaints due to long waiting time is reduced, thereby solving the technical problem that the relevant technology does not deploy the splitter in the target area in advance, resulting in a large number of work orders to be transferred to waiting for installation in the target area at the same time.

[0118] Example 3

[0119] Based on Embodiment 1 of the present application, an embodiment of a device for determining a splitter deployment scheme is also provided, and the device executes the above-mentioned method for determining a splitter deployment scheme of the above-mentioned embodiment when running. Figure 4 is a schematic diagram of a structure of an optional device for determining a splitter deployment scheme according to an embodiment of the present application, such as Figure 4 As shown, the device for determining the optical splitter deployment scheme includes at least a first prediction module 42, a first determination module 44, a second prediction module 46 and a second determination module 48, wherein:

[0120] The first prediction module 42 is used to obtain the first installed quantity of network communication devices installed in multiple sub-areas in the target area within the current timestamp, and use the pre-trained first prediction model to analyze the first installed quantity of each sub-area within the current timestamp to obtain the predicted installed quantity corresponding to each sub-area within the first time period, wherein the first time period is any time period after the current timestamp;

[0121] A first determination module 44 is used to determine a plurality of initial deployment schemes according to the predicted number of installed devices corresponding to each sub-area in the first time period and the first number of pre-deployed optical splitters in the target area;

[0122] The second prediction module 46 is used to determine, for each initial deployment plan, the non-coverage rate of the splitter resources when each sub-area deploys the splitter according to the initial deployment plan, and use the pre-trained second prediction model to analyze the predicted installed quantity and the non-coverage rate of the splitter resources of each sub-area in the first time period, to obtain the predicted number of work orders to be installed corresponding to each sub-area when the splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of the splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that do not cover the operator's business in the sub-area at the current timestamp;

[0123] The second determination module 48 is used to determine a target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted number of work orders to be installed in all sub-areas in the target area in the first time period less than a first threshold.

[0124] It should be noted that the various modules in the above-mentioned spectrometer deployment plan determination device can be a program module (for example, a set of program instructions that implement a certain specific function) or a hardware module. For the latter, it can be expressed in the following forms, but is not limited to this: the expression form of each of the above-mentioned modules is a processor, or the functions of each of the above-mentioned modules are implemented by a processor.

[0125] Example 4

[0126] Based on Embodiment 2 of the present application, an embodiment of a device for determining a splitter deployment scheme is also provided, and the device executes the above-mentioned method for determining a splitter deployment scheme of the above-mentioned embodiment when running. Figure 5 is a schematic diagram of the structure of another optional device for determining a splitter deployment scheme according to an embodiment of the present application, such as Figure 5 As shown, the device for determining the optical splitter deployment scheme includes at least a third prediction module 52, a third determination module 54, a fourth prediction module 56 and a fourth determination module 58, wherein:

[0127] The third prediction module 52 is used to obtain the first installed quantity of network communication equipment installed in multiple sub-areas in the target area within the current timestamp, and determine the predicted installed quantity corresponding to each sub-area in the first time period according to the first installed quantity of each sub-area within the current timestamp;

[0128] A third determination module 54 is used to determine a plurality of initial deployment schemes according to the predicted number of installed devices corresponding to each sub-area in the first time period and the first number of pre-deployed optical splitters in the target area;

[0129] The fourth prediction module 53 is used to determine, for each initial deployment plan, the non-coverage rate of the splitter resources when each sub-area deploys the splitter according to the initial deployment plan, and determine the number of predicted work orders corresponding to each sub-area when the splitter is deployed according to the initial deployment plan in the first time period based on the predicted number of installations in each sub-area in the first time period and the non-coverage rate of the splitter resources, wherein the non-coverage rate of the splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that do not cover the operator's business in the sub-area within the current timestamp;

[0130] The fourth determination module 58 is used to determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted number of work orders to be transferred to installation in all sub-areas in the target area in the first time period less than a first threshold.

[0131] It should be noted that the various modules in the above-mentioned spectrometer deployment plan determination device can be a program module (for example, a set of program instructions that implement a certain specific function) or a hardware module. For the latter, it can be expressed in the following forms, but is not limited to this: the expression form of each of the above-mentioned modules is a processor, or the functions of each of the above-mentioned modules are implemented by a processor.

[0132] Example 5

[0133] According to an embodiment of the present application, a non-volatile storage medium is also provided, in which a program is stored, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute the method for determining the splitter deployment scheme in Example 1 and the method for determining the splitter deployment scheme in Example 2.

[0134] Optionally, the device where the non-volatile storage medium is located implements the following steps by running the program: obtaining a first installed quantity of network communication devices installed in multiple sub-areas in the target area within a current timestamp, and using a pre-trained first prediction model to analyze the first installed quantity of each sub-area within the current timestamp to obtain a predicted installed quantity corresponding to each sub-area within a first time period, wherein the first time period is any time period after the current timestamp; determining multiple initial deployment plans based on the predicted installed quantity corresponding to each sub-area within the first time period and a first quantity of pre-deployed optical splitters in the target area; for each initial deployment plan, determining the optical splitter resource non-coverage rate when each sub-area deploys the optical splitter according to the initial deployment plan, and using The pre-trained second prediction model analyzes the predicted installed quantity and the non-coverage rate of the splitter resources of each sub-area in the first time period, and obtains the predicted number of work orders to be installed corresponding to each sub-area when the splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of the splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area in the current timestamp; determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted number of work orders to be installed of all sub-areas in the target area in the first time period less than a first threshold.

[0135] Optionally, the device where the non-volatile storage medium is located implements the following steps by running the program: obtaining a first installed quantity of network communication devices installed in multiple sub-areas in the target area within a current timestamp, and determining a predicted installed quantity corresponding to each sub-area in a first time period according to the first installed quantity of each sub-area in the current timestamp; determining multiple initial deployment plans according to the predicted installed quantity corresponding to each sub-area in the first time period and a first quantity of pre-deployed optical splitters in the target area; for each initial deployment plan, determining a non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the initial deployment plan, and determining a predicted installed quantity corresponding to each sub-area in the first time period according to the predicted installed quantity corresponding to each sub-area in the first time period. The predicted number of installed devices and the non-coverage rate of splitter resources are used to determine the predicted number of work orders to be transferred to installation in each sub-area when the splitter is deployed according to the initial deployment plan within the first time period, wherein the non-coverage rate of splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area within the current timestamp; determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted numbers of work orders to be transferred to installation in all sub-areas within the target area within the first time period less than a first threshold.

[0136] According to an embodiment of the present application, a computer program product is also provided, which includes a stored computer program, wherein when the computer program is executed by a processor, the method for determining the splitter deployment scheme in Example 1 and the method for determining the splitter deployment scheme in Example 2 are implemented.

[0137] Optionally, the computer program executes the following steps: obtaining a first installed quantity of network communication equipment installed in multiple sub-areas in the target area within a current timestamp, and using a pre-trained first prediction model to analyze the first installed quantity of each sub-area within the current timestamp to obtain a predicted installed quantity corresponding to each sub-area within a first time period, wherein the first time period is any time period after the current timestamp; determining multiple initial deployment plans based on the predicted installed quantity corresponding to each sub-area within the first time period and a first quantity of pre-deployed optical splitters in the target area; for each initial deployment plan, determining a non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the initial deployment plan, and using a pre-trained second prediction model to obtain a predicted installed quantity corresponding to each sub-area within a first time period; The prediction model analyzes the predicted number of installations and the non-coverage rate of splitter resources in each sub-area in the first time period, and obtains the predicted number of work orders to be installed corresponding to each sub-area when the splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area in the current timestamp; determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted number of work orders to be installed of all sub-areas in the target area in the first time period less than a first threshold.

[0138] Optionally, the computer program executes the following steps: obtaining a first installed quantity of network communication devices installed in multiple sub-areas in the target area within a current timestamp, and determining a predicted installed quantity corresponding to each sub-area in a first time period according to the first installed quantity of each sub-area in the current timestamp; determining multiple initial deployment plans according to the predicted installed quantity corresponding to each sub-area in the first time period and a first quantity of pre-deployed optical splitters in the target area; for each initial deployment plan, determining a non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the initial deployment plan, and determining a predicted installed quantity corresponding to each sub-area in the first time period according to the predicted installed quantity corresponding to each sub-area in the first time period; determining a first quantity of pre-deployed optical splitters in the target area ... The method comprises the following steps: determining the predicted number of work orders to be transferred to installation for each sub-area when the splitter is deployed according to the initial deployment plan in the first time period based on the quantity and the non-coverage rate of the splitter resources, wherein the non-coverage rate of the splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area at the current timestamp; and determining the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted number of work orders to be transferred to installation for all sub-areas in the target area in the first time period less than a first threshold. According to an embodiment of the present application, a processor is also provided, the processor being used to run a program, wherein the method for determining the splitter deployment plan in Example 1 and the method for determining the splitter deployment plan in Example 2 are executed when the program is running.

[0139] Optionally, when the program is running, the following steps are executed: obtaining a first installed quantity of network communication equipment installed in multiple sub-areas in the target area within the current timestamp, and using a pre-trained first prediction model to analyze the first installed quantity of each sub-area within the current timestamp to obtain a predicted installed quantity corresponding to each sub-area within a first time period, wherein the first time period is any time period after the current timestamp; determining multiple initial deployment plans based on the predicted installed quantity corresponding to each sub-area within the first time period and a first quantity of pre-deployed optical splitters in the target area; for each initial deployment plan, determining a non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the initial deployment plan, and using a pre-trained second prediction model to obtain a predicted installed quantity corresponding to each sub-area within a first time period; The measurement model analyzes the predicted installed quantity and the non-coverage rate of the splitter resources of each sub-area in the first time period, and obtains the predicted number of work orders to be installed corresponding to each sub-area when the splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of the splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area in the current timestamp; determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted numbers of work orders to be installed of all sub-areas in the target area in the first time period less than a first threshold.

[0140] Optionally, when the program is running, the following steps are executed: obtaining a first installed quantity of network communication equipment installed in multiple sub-areas in the target area within the current timestamp, and determining a predicted installed quantity corresponding to each sub-area in the first time period according to the first installed quantity of each sub-area in the current timestamp; determining multiple initial deployment plans according to the predicted installed quantity corresponding to each sub-area in the first time period and the first quantity of pre-deployed optical splitters in the target area; for each initial deployment plan, determining the non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the initial deployment plan, and determining the predicted installed quantity corresponding to each sub-area in the first time period according to the predicted installed quantity and the splitter resource coverage rate to determine the predicted number of work orders to be transferred to installation in each sub-area when the splitter is deployed according to the initial deployment plan within the first time period, wherein the splitter resource coverage rate is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area within the current timestamp; determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted numbers of work orders to be transferred to installation in all sub-areas within the target area within the first time period less than a first threshold.

[0141] According to an embodiment of the present application, an electronic device is also provided, wherein: Figure 6 is a schematic diagram of the structure of an optional electronic device according to an embodiment of the present application, such as Figure 6 As shown, the electronic device includes one or more processors; a memory for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors are implemented to run the programs, wherein the programs are configured to execute the method for determining the splitter deployment scheme in the above-mentioned embodiment 1 and the method for determining the splitter deployment scheme in embodiment 2 when running.

[0142] Optionally, the processor is configured to implement the following steps through a computer program: obtaining a first installed quantity of network communication equipment installed in multiple sub-areas in the target area within a current timestamp, and using a pre-trained first prediction model to analyze the first installed quantity of each sub-area within the current timestamp to obtain a predicted installed quantity corresponding to each sub-area within a first time period, wherein the first time period is any time period after the current timestamp; determining multiple initial deployment plans based on the predicted installed quantity corresponding to each sub-area within the first time period and a first quantity of pre-deployed optical splitters in the target area; for each initial deployment plan, determining a non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the initial deployment plan, and using the pre-trained first prediction model to obtain a predicted installed quantity corresponding to each sub-area within a first time period; wherein the first time period is any time period after the current timestamp; determining multiple initial deployment plans based on the predicted installed quantity corresponding to each sub-area within the first time period and a first quantity of pre-deployed optical splitters in the target area; and determining, for each initial deployment plan, a non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the initial deployment plan, and using the pre-trained first prediction model to obtain a predicted installed quantity corresponding to each sub-area within a first time period. The second prediction model trained is used to analyze the predicted installed quantity and the non-coverage rate of splitter resources of each sub-area in the first time period, and obtain the predicted number of work orders to be installed corresponding to each sub-area when the splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area in the current timestamp; determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted numbers of work orders to be installed of all sub-areas in the target area in the first time period less than a first threshold.

[0143] Optionally, the processor is configured to implement the following steps by executing a computer program: obtaining a first installed quantity of network communication devices installed in multiple sub-areas in the target area within a current timestamp, and determining a predicted installed quantity corresponding to each sub-area in a first time period according to the first installed quantity of each sub-area in the current timestamp; determining multiple initial deployment plans according to the predicted installed quantity corresponding to each sub-area in the first time period and a first quantity of pre-deployed optical splitters in the target area; for each initial deployment plan, determining a non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the initial deployment plan, and determining a predicted installed quantity corresponding to each sub-area in the first time period according to the predicted installed quantity corresponding to each sub-area in the first time period and a first quantity of pre-deployed optical splitters in the target area; and determining a predicted installed quantity corresponding to each sub-area in the first time period according to the predicted installed quantity corresponding to each sub-area in the first time period. The number of installed devices and the non-coverage rate of splitter resources are measured to determine the predicted number of work orders to be transferred to installation in each sub-area when the splitter is deployed according to the initial deployment plan within the first time period, wherein the non-coverage rate of splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses that are not covered by the operator's business in the sub-area within the current timestamp; determine the target deployment plan for each sub-area in the first time period from multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted numbers of work orders to be transferred to installation in all sub-areas within the target area within the first time period less than a first threshold.

[0144] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0145] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0146] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0147] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0148] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0149] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0150] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining a splitter deployment plan, characterized in that: include: Obtaining a first installed quantity of network communication equipment installed in multiple sub-areas within a target area within a current timestamp, and using a pre-trained first prediction model to analyze the first installed quantity of each sub-area within the current timestamp, to obtain a predicted installed quantity corresponding to each sub-area within a first time period, wherein the first time period is any time period after the current timestamp; Determine a plurality of initial deployment plans according to the predicted number of installed devices corresponding to each sub-area in the first time period and the first number of pre-deployed optical splitters in the target area; For each of the initial deployment plans, determine the non-coverage rate of the splitter resources when each of the sub-areas deploys the splitter according to the initial deployment plan, and use the pre-trained second prediction model to analyze the predicted installed quantity and the non-coverage rate of the splitter resources of each of the sub-areas in the first time period, and obtain the predicted number of work orders to be installed corresponding to each of the sub-areas when the splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of the splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses of the operator's business that are not covered by the sub-area in the current timestamp; A target deployment plan for each sub-area in the first time period is determined from the multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted numbers of work orders to be installed of all sub-areas in the target area in the first time period less than a first threshold.

2. The method according to claim 1, characterized in that The training process of the first prediction model includes: Acquire multiple groups of first sample data, wherein the first sample data includes: a second installed quantity of a target sub-region within the target region within a past timestamp and a third installed quantity of the target sub-region within a second time period, wherein the second time period is any time period after the past timestamp, and the target sub-region is any sub-region among multiple sub-regions within the target region; Constructing a first neural network model, wherein the first neural network model at least includes: an encoding layer, an input layer, a hidden layer, and an output layer; The first neural network model is iteratively trained using multiple groups of the first sample data to obtain the first prediction model.

3. The method according to claim 1, characterized in that The first number of pre-deployed optical splitters in the target area meets the following conditions: The first quantity does not exceed a preset quantity; A second ratio of the sum of the total number of ports of the first number of splitters and the total number of vacant ports of the splitters deployed in the target area within the current timestamp divided by the total number of ports of the splitters deployed in the target area within the current timestamp does not exceed a preset port vacancy rate.

4. The method according to claim 1, characterized in that: Determining a plurality of initial deployment schemes according to the predicted installed capacity of each sub-area in a future time period and the first quantity of pre-deployed optical splitters in the target area includes: For each of the sub-areas, determining a third ratio of the predicted number of installed capacity in the sub-area in the first time period to a third number of standard addresses in the sub-area that are not covered by the operator's service in the current timestamp; determining whether the third ratio is less than a preset second threshold, and determining whether a fourth number of optical splitters to be deployed in the sub-area is zero according to the comparison result; The first number of optical splitters to be deployed in at least one of the sub-areas is deployed according to whether the fourth number of optical splitters to be deployed in each of the sub-areas is zero, so as to obtain a plurality of the initial deployment schemes.

5. The method according to claim 1, characterized in that: Determining the non-coverage rate of optical splitter resources when the optical splitters are deployed in each of the sub-areas according to the initial deployment plan includes: Determining a fourth number of optical splitters deployed in each of the sub-areas defined in the initial deployment plan and a fifth number of standard addresses covered by each of the optical splitters; For each of the sub-areas, determine the sixth number of standard addresses of the sub-area that are not covered by the splitter in the current timestamp, determine the product of the fourth number and the fifth number, and use the difference between the sixth number and the obtained product as the second number; determine a second ratio of the second number to the third number of standard addresses of the operator's business that are not covered in the sub-area in the current timestamp; use the second ratio as the splitter resource coverage rate when the sub-area deploys the splitter according to the initial deployment plan.

6. The method according to claim 1, characterized in that The training process of the second prediction model includes: Acquire multiple groups of second sample data, wherein the second sample data includes: the number of installations and the non-coverage rate of optical splitter resources in the target sub-area within the target area in the past timestamp, and the number of work orders transferred to be installed in the target sub-area within the second time period, and the target sub-area is any sub-area among the multiple sub-areas within the target area, and the second time period is any time period after the past timestamp; Constructing a second neural network model, wherein the second neural network model at least includes: an encoding layer, an input layer, a hidden layer, and an output layer; The second neural network model is iteratively trained using multiple groups of the second sample data to obtain the second prediction model.

7. The method according to claim 1, characterized in that Before analyzing the predicted installed capacity and the non-coverage rate of optical splitter resources in each of the sub-areas in the first time period by using the pre-trained second prediction model, the method further includes: Determine the average value and standard deviation value of the installed capacity of all the sub-areas in the target area during the first time period; The predicted installed capacity of each of the sub-regions in the first time period is standardized using the mean value and the standard deviation value.

8. A method for determining a splitter deployment plan, characterized in that: include: Obtaining a first installed capacity of network communication devices in multiple sub-areas within a target area within a current timestamp, and determining a predicted installed capacity corresponding to each sub-area within a first time period according to the first installed capacity of each sub-area within the current timestamp; Determine a plurality of initial deployment plans according to the predicted number of installed devices corresponding to each sub-area in the first time period and the first number of pre-deployed optical splitters in the target area; For each of the initial deployment plans, determine the non-coverage rate of splitter resources when each of the sub-areas deploys splitters according to the initial deployment plan, and determine the predicted number of work orders to be installed corresponding to each of the sub-areas when the splitters are deployed according to the initial deployment plan in the first time period based on the predicted number of installations of each sub-area in the first time period and the non-coverage rate of splitter resources, wherein the non-coverage rate of splitter resources is a first ratio of a second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to a third number of standard addresses of the operator's business that are not covered by the sub-area in the current timestamp; A target deployment scheme for each sub-area in the first time period is determined from the multiple initial deployment schemes, wherein the target deployment scheme is a deployment scheme that makes the sum of the predicted numbers of work orders to be installed in all sub-areas in the target area in the first time period less than a first threshold.

9. A device for determining a splitter deployment plan, characterized in that: include: A first prediction module is used to obtain a first installed quantity of network communication equipment installed in multiple sub-areas in the target area within a current timestamp, and analyze the first installed quantity of each sub-area within the current timestamp using a pre-trained first prediction model to obtain a predicted installed quantity corresponding to each sub-area within a first time period, wherein the first time period is any time period after the current timestamp; A first determination module, configured to determine a plurality of initial deployment schemes according to the predicted number of installed devices corresponding to each sub-area in the first time period and the first number of pre-deployed optical splitters in the target area; A second prediction module is used to determine, for each of the initial deployment plans, a non-coverage rate of splitter resources when each of the sub-areas deploys splitters according to the initial deployment plan, and use a pre-trained second prediction model to analyze the predicted number of installed devices and the non-coverage rate of splitter resources for each of the sub-areas in the first time period, to obtain the predicted number of work orders to be installed corresponding to each of the sub-areas when the splitters are deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of splitter resources is a first ratio of a second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to a third number of standard addresses that do not cover the operator's business in the sub-area at a current timestamp; The second determination module is used to determine the target deployment plan for each sub-area in the first time period from the multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted number of work orders to be installed in all sub-areas in the target area in the first time period less than a first threshold.

10. A device for determining a splitter deployment plan, characterized in that: include: A third prediction module is used to obtain a first installed capacity of network communication devices installed in multiple sub-areas within the target area within a current timestamp, and determine a predicted installed capacity corresponding to each sub-area within a first time period according to the first installed capacity of each sub-area within the current timestamp; A third determination module is used to determine a plurality of initial deployment schemes according to the predicted installed capacity corresponding to each sub-area in the first time period and the first number of pre-deployed optical splitters in the target area; A fourth prediction module is used to determine, for each of the initial deployment plans, the non-coverage rate of the splitter resources when each of the sub-areas deploys the splitter according to the initial deployment plan, and determine, based on the predicted number of installations of each of the sub-areas in the first time period and the non-coverage rate of the splitter resources, the number of predicted work orders to be installed corresponding to each of the sub-areas when the splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of the splitter resources is a first ratio of the second number of standard addresses that are still not covered by the splitter after the sub-area deploys the splitter according to the initial deployment plan to the third number of standard addresses of the operator's business that are not covered by the sub-area in the current timestamp; The fourth determination module is used to determine the target deployment plan for each sub-area in the first time period from the multiple initial deployment plans, wherein the target deployment plan is a deployment plan that makes the sum of the predicted number of work orders to be transferred to installation in all sub-areas in the target area in the first time period less than a first threshold.

11. A computer program product, characterized in that include: A computer program, wherein when the computer program is executed by a processor, the method for determining a splitter deployment scheme according to any one of claims 1 to 8 is implemented.

12. An electronic device, characterized in that: include: A memory and a processor, wherein the processor is used to run a program stored in the memory, wherein the program executes the method for determining a splitter deployment plan according to any one of claims 1 to 8 when running.

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