Method and device for determining optical splitter deployment plan

Abstract

The present application discloses a method and device for determining a deployment plan for a spectrometer. The method includes: obtaining the first installed quantity of multiple sub-areas in the target area at the current timestamp, and using a first prediction model to analyze the first installed quantity of each sub-area to obtain the predicted installed quantity of each sub-area in the first time period; determining multiple deployment plans based on the predicted installed quantity of each sub-area and the number of pre-deployed spectrometers in the target area; for each deployment plan, determining the non-coverage rate of spectrometer resources for each sub-area in which the spectrometers are deployed according to the deployment plan, and using a second prediction model to analyze the predicted installed quantity and non-coverage rate of spectrometer resources for each sub-area to obtain the predicted number of work orders to be transferred to be installed in each sub-area, and based on this, determining the target deployment plan from multiple deployment plans. The present application solves the technical problem that the related technology does not deploy the spectrometers 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.

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, some households may encounter the problem of no network resources supporting the service at the installation address when applying for new installation or relocation services such as broadband, landline, and IPTV (Interactive Personal Video Television). 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 limitations of the connection medium, the standard addresses that a splitter can cover are limited. If sufficient splitters are built in advance within a region to support installation needs at all locations, this will not only significantly increase construction costs but also create a large number of idle resources. However, if splitter resources are not deployed in advance, a large number of work orders will be transferred to pending installation. Therefore, how to reasonably deploy splitters in advance to reduce the number of work orders transferred to pending installation while considering port resource utilization within a limited cost framework is an urgent problem that needs to be solved.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0005] The embodiments of the present application provide a method and apparatus for determining a splitter deployment plan, to at least solve the technical problem that in the related art, splitters in a target area are not deployed in advance, resulting in a large number of work orders to be transferred to 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 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; determining 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; for each initial deployment plan, determining the splitter resource non-coverage rate when each sub-area deploys the splitter according to the initial deployment plan, and using The pre-trained second prediction model is used to analyze the predicted number of installations and the non-coverage rate of spectrometer resources in each sub-area in the first time period, and 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 is obtained, wherein the non-coverage rate of spectrometer resources is a first ratio of the second number of standard addresses that are still not covered by the spectrometer after the sub-area pre-deploys the spectrometer 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; 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.

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

[0008] Optionally, the first number of pre-deployed optical splitters in the target area satisfies the following conditions: the first number does not exceed a preset number; and 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.

[0009] Optionally, multiple initial deployment plans are determined based on the predicted installed capacity of each sub-area in a 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 within 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 not covered by the operator's business in the sub-area within the current timestamp; and taking the second ratio as the non-coverage rate of splitter resources when the sub-area deploys the splitter according to the initial deployment plan.

[0011] Optionally, the training process of the second prediction model includes: obtaining multiple sets of second sample data, wherein the second sample data includes: 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: an encoding layer, an input layer, a hidden layer, and an output layer; using multiple sets 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 non-coverage rate of each sub-area in the first time period, the method also includes: determining the average value and standard deviation of the installed capacity of all sub-areas in the target area in the first time period; and using the average value and standard deviation value 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, comprising: obtaining a first installed quantity of network communication equipment installed in multiple sub-areas within a target area within a current timestamp, and determining a predicted installed quantity corresponding to each sub-area within a first time period based on the first installed quantity of each sub-area within 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 the first quantity of pre-deployed splitters within the target area; for each initial deployment plan, determining a splitter resource non-coverage rate when each sub-area deploys the splitter according to the initial deployment plan, and determining a predicted installed quantity corresponding to each sub-area within the first time period based on the predicted installed quantity corresponding to each sub-area within the first time period and the first quantity of pre-deployed splitters within the target area; determining a predicted installed quantity corresponding to each sub-area within the first time period based on the predicted installed quantity corresponding to each sub-area within the first time period and the first quantity of pre-deployed splitters within the target area; determining a predicted installed quantity corresponding to each sub-area within the first time period based on the predicted installed quantity corresponding to each sub-area within the first time period; determining a ... 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 in 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, configured to obtain a first installed quantity of network communication equipment installed in multiple sub-areas within 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 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 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, configured to determine, for each initial deployment plan, the number of splitters in each sub-area when deploying the splitters 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 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, wherein the non-coverage rate of the spectrometer resources is a first ratio of the second number of standard addresses that are still not covered by the spectrometer after the sub-area deploys the spectrometer 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 further provided, including: a third prediction module, configured to obtain a first installed quantity of network communication equipment installed in multiple sub-areas within a target area within a current timestamp, and determine a predicted installed quantity corresponding to each sub-area within a first time period based on the first installed quantity of each sub-area within the current timestamp; a third determination module, configured 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 within the target area; a fourth prediction module, configured to determine, for each initial deployment plan, a splitter resource non-coverage rate when each sub-area deploys splitters according to the initial deployment plan, and determine the splitter resource non-coverage rate based on each initial deployment plan. The predicted number of installed devices in each sub-area in the first time period and the non-coverage rate of the spectrometer resources determine 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, wherein the non-coverage rate of the spectrometer resources is a first ratio of the second number of standard addresses that are still not covered by the spectrometer after the sub-area deploys the spectrometer 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 solution is implemented.

[0017] According to another aspect of an embodiment of the present application, an electronic device is provided, 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 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 period; then, under the premise of a certain number of spectrometers, multiple initial deployment plans are designed according to the predicted installed quantity of each sub-area in the target area in the future period; then, the spectrometer resource non-coverage rate of each sub-area when the spectrometers are deployed according to each spectrometer deployment plan is calculated, and the predicted installed quantity and spectrometer resource non-coverage rate of each sub-area in the first time period are analyzed using a second prediction model. The predicted number of work orders transferred to waiting for 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 transferred to waiting for 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 transferred to waiting for installation in the 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 transferred to waiting for 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 This is a hardware structure block diagram of a computer terminal (or mobile device) for implementing a method for determining a splitter deployment solution according to an embodiment of the present application;

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

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

[0023] Figure 4 is a 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 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 structural diagram 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 present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this 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 sequential order. 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 a sequence 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 the 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] An optical splitter is a passive device used to split and combine optical wave energy, effectively distributing downlink data and concentrating uplink data. Typically, an optical splitter has one uplink port and multiple downlink ports, each of which can connect to a household optical modem.

[0031] Transfer to installation work order: refers to the initiation of installation services at the standard address (i.e. the user's installation address) but at an address that is not covered by the 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 the transfer to installation work order is completed, the installation of the splitter is completed and the installation address is covered. 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 related technologies, some users encounter the problem of a lack of optical splitter resources at the installation address (i.e., the address where the user initiates the installation or relocation service) when applying for new broadband, fixed-line, or IPTV services. A common solution in this situation is: first, the resource configuration personnel initiates a transfer work order; then, after receiving the transfer work order, the optical splitter layout personnel will go to the installation address to install the optical splitter, thereby providing the optical splitter resources for the installation address; finally, after the work order is completed (the optical 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 optical splitter. However, this method of installing optical splitter resources after the user submits the service application significantly increases the user's service processing waiting time, resulting in reduced user satisfaction and even complaints.

[0034] In order to solve this problem, relevant solutions are provided in the embodiments of the present application, which are 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 plan is shown. Figure 1As shown, the computer terminal 10 (or mobile device 10) may include one or more (illustrated as 102a, 102b, ..., 102n) 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 will 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 than 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 circuitry". The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuitry may be a single independent processing module, or may be incorporated in whole or in part into any of the other components of the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuitry serves 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 optical splitter deployment plan 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, thereby implementing the method for determining the optical splitter deployment plan of the above-mentioned application. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory remotely located 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 configured to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the communications provider of the computer terminal 10. In one embodiment, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device 106 may be a radio frequency (RF) module, which is configured 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 FIG. 1 is a flow chart of an optional method for determining a splitter deployment solution according to an embodiment of the present application, such as Figure 2 As shown, the method includes at least steps S202-S208, wherein:

[0042] Step S202: Obtain the first installed quantity of network communication equipment installed in multiple sub-areas within 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.

[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 applying for new installation or relocation services for broadband, landline, 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 to obtain the predicted number of installed units 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 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.

[0045] In the technical solution provided in step S204, multiple initial deployment plans are first formulated based on the first number of optical splitters to be deployed in the target area and the predicted number of optical splitters installed in each sub-area during the first time period. Each initial deployment plan defines that the total number of optical splitters installed in all sub-areas is equal to the first number, and the number of optical splitters installed in each sub-area is greater than or equal to zero and less than the first number.

[0046] Step S206: For each initial deployment plan, determine the non-coverage rate of spectrometer resources when each sub-area deploys spectrometers according to the initial deployment plan, and use the pre-trained second prediction model to analyze the predicted installed quantity and non-coverage rate of spectrometer resources in each sub-area within 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 within the first time period.

[0047] In the technical solution provided in step S206, each initial deployment plan is analyzed to determine the optical splitter resource coverage ratio for each sub-region when the optical splitter is deployed according to the initial deployment plan. The optical splitter resource coverage ratio is a first ratio of a second number of standard addresses that are still not covered by the optical splitter after the optical splitter is deployed in the sub-region according to the initial deployment plan to a third number of standard addresses for operator services that are not covered in the sub-region at the current timestamp. A second prediction model is then used to analyze the predicted number of installations and the optical splitter resource coverage ratio for each sub-region during the first time period to obtain a predicted number of work orders to be transferred to installation for each sub-region when the optical splitter is deployed according to the initial deployment plan during the first time period.

[0048] Step S208: determining a target deployment plan for each sub-area in the first time period from 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 so that 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 is 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 step S202 above, the first prediction model is also called an installation quantity (IQ) prediction model, and its training process may include:

[0052] Step 1: Obtain multiple sets 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) within 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) within 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 includes at least: an encoding layer, an input layer, a hidden layer (multiple layers in total), and an output layer. The encoding layer encodes the input information (i.e., the second installed capacity of the target sub-region within the past timestamp), the hidden layer processes and extracts features from the encoded information, and the output layer generates the final predicted installed capacity based on the output of the hidden layer.

[0057] Step 3: Use multiple sets 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; the 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-region within the current timestamp to obtain the predicted installed quantity corresponding to each sub-region within the first time period.

[0060] For each sub-region, the number of installed units in different timestamps is different. Therefore, the coding layer can be used to number the sub-regions g i For geographic location coding, the embodiment of the present application uses a one-hot algorithm 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 time information encoding, in this embodiment of the application, the features of the timestamp t can be extracted and spliced ​​into a vector V with a dimension of 26 t ∈R 26 The extracted time features are encoded using a one-hot algorithm, including the month of the year, the week of the month, the day 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], [0,0,1,0,0,0], [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 used 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 a predicted installed capacity of 20 for sub-region g1 in the first time period of the future. In this way, the installed capacity of the other five sub-regions g2, g3, g4, g5, and g6 in the first time period of 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 can run the first prediction model. The raw data of the first prediction model refers to unprocessed data, and generally 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 intermediate layers or between neurons. Specifically, the structural data can include code related to the structure of the first prediction model, such as code for performing related calculations between intermediate layers or between neurons.

[0064] In one embodiment, a memory area for loading the first prediction model can be divided, including a structure data storage area and a parameter storage area. The structure data storage area is used to store structure-related code, and the parameters referenced therein can point to the addresses of specific parameters in the parameter storage area through pointers. During the training of the first prediction model, parameters may need to be frequently updated, and the parameter values ​​in the parameter storage area can be simply updated.

[0065] As an optional implementation, in the technical solution provided in step S204 above, 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 the maximum quantity N′ that can be purchased within 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 subregion 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 at the current timestamp; Represents subregion g iThe number of ports on the optical splitter at timestamp t, Indicates the total number of optical splitter ports deployed in the target area at 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 step S204 above, the method may include:

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

[0075] The third number of standard addresses of the operator's business that are not covered by the above sub-area at 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 the fourth number of optical splitters to be deployed in the sub-area is zero based on 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 gi =0; otherwise, In the case of i The fourth number r of optical splitters to be deployed 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] In other words, based on whether the number of optical splitters to be deployed in each sub-area is zero, a permutation and combination method is used to determine whether the first number of optical splitters will be deployed in at least one sub-area, thereby obtaining multiple initial deployment plans. This is done to prevent deployment plans that favor deploying optical splitters in sub-areas where the predicted number of installed base units is significantly smaller than the number of unserved service addresses from yielding lower returns. Therefore, when determining the initial deployment plan, optical splitters will not be deployed in such sub-areas, thereby optimizing deployment efficiency with minimal performance loss.

[0080] For example, based on 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 third ratios of the six sub-areas g1, g2, g3, g4, g5, and g6 are determined by the predicted number of installed capacity 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 that α = 0.05, and Therefore, the number of optical splitters deployed in sub-regions g1, g3, and g6 is zero. Therefore, for the six grids mentioned above, there are 10 possible initial deployment schemes: (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), and (0,3,0,0,0,0). The (0,0,0,1,2,0) scheme means that zero optical splitters are deployed in g1, g2, g3, and g6, one optical splitter is deployed in g4, and two optical splitters are deployed in g5.

[0082] As an optional implementation, in the technical solution provided in step S206 above, the process of determining the optical splitter resource coverage ratio 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 of the operator's business 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 time period in the future giThe total number of standard addresses that can be covered by the optical splitter. 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 optical splitter resource coverage ratio 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] Furthermore, as an optional implementation, in the technical solution provided in step S206 above, 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 optical splitter resource non-coverage rate of 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 includes at least: an encoding layer, an input layer, a hidden layer (multiple layers in total), and an output layer. The encoding layer encodes the input information (the number of installations in the target sub-region and the optical splitter resource coverage ratio in the past timestamp), the hidden layer processes and extracts features from the encoded 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 spectrometer resource non-coverage rate of 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 installed 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 installed in the sub-area in the second time period and the number of work orders to be installed 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 a 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 can run the second prediction model. The raw data of the second prediction model refers to unprocessed data, and generally includes 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 intermediate layers or between neurons. Specifically, the structural data can include code related to the structure of the second prediction model, such as code for performing related calculations between intermediate layers or between neurons.

[0096] In one embodiment, a memory area for loading the second prediction model can be divided, including a structure data storage area and a parameter storage area. The structure data storage area is used to store structure-related code, and the parameters referenced therein can point to the addresses of specific parameters in the parameter storage area through pointers. During the training of the second prediction model, parameters may need to be frequently updated, and the parameter values ​​in the parameter storage area can be simply updated.

[0097] For example, for the target sub-region g1 within the target region A, its geographical location information, time information, standardized installed capacity and spectrometer resource coverage rate are encoded and concatenated to obtain the input vector This is then input into the second prediction model to obtain a predicted number of work orders transferred to pending installation for target sub-region g1 during the first time period: 2. Similarly, the number of installations for the other five sub-regions g2, g3, g4, g5, and g6 during the first time period is calculated to be 3, 0, 2, 9, and 2, respectively. Therefore, the total number of work orders transferred to pending installation for target region 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 optical splitter resources in each sub-region during the first time period. Prior to this, since the non-coverage rate of optical splitter resources is an input feature, its value range is between 0 and 1, so it does not need to be processed; while 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 for all sub-regions within the target region during the first time period.

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

[0101]

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

[0103] The technical solution provided in step S206 above can be used to obtain the predicted number of work orders transferred to pending installation for each sub-area within the target area when deploying optical splitters according to each initial deployment plan during the first time period, i.e., the total number of work orders transferred to pending installation for the entire area under each initial deployment plan. To minimize the number of work orders transferred to pending installation and reduce the average installation wait time for users, a target deployment plan can be selected from the multiple initial deployment plans. This target deployment plan is the deployment plan that ensures that the sum of the predicted number of work orders transferred to pending installation for all sub-areas within the target area during the first time period is less than a first threshold.

[0104] For example, if the six sub-areas g1, g2, g3, g4, g5, and g6 within target area A deploy optical splitters according to the 10 initial deployment plans described above, the minimum number of work orders transferred to pending installation is 11, and the corresponding allocation plan is (0, 0, 0, 1, 2, 0). Therefore, under the premise that the first number of optical splitters to be deployed is limited to 3, deploying two optical splitters in sub-area g4 and one optical splitter in sub-area g5 can minimize the number of work orders transferred to pending installation in the first future time period, thereby reducing users' average installation wait time and lowering 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 optical splitter resources for all standard addresses in the target area in advance to reduce the number of resource transfer work orders, and 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 spectrometers, 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 optical splitter resource non-coverage rate of each sub-area when the spectrometer is deployed according to each spectrometer 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 transferred to waiting for installation when each sub-area deploys splitters 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 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 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 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 FIG. 1 is a flow chart of an optional method for determining a splitter deployment solution according to an embodiment of the present application, such as Figure 3 As shown, the method includes at least steps S302-S308, wherein:

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

[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 the spectrometer resources when each sub-area deploys the spectrometer according to the initial deployment plan, and determine the corresponding predicted number of work orders to be transferred to installation when each sub-area deploys the spectrometer according to the initial deployment plan in the first time period based on the predicted installed quantity and the non-coverage rate of the spectrometer 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 deploying the spectrometer according to the initial deployment plan within the first time period based on the predicted installed quantity and the spectrometer resource non-coverage rate of each sub-area within the first time period 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 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 within the target area predicted to be less than a first threshold within the first time period.

[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 embodiment of the present application will not elaborate on the specific implementation methods of steps S302-S308.

[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, and 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 splitter resource non-coverage rate of each sub-area when the splitter is deployed according to each splitter deployment scheme is calculated , 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 transferred to waiting for installation when each sub-area deploys splitters 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 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 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 transferred to waiting for installation in the target area at the same time.

[0118] Example 3

[0119] Based on the embodiment 1 of the present application, an embodiment of a device for determining a splitter deployment plan is also provided, and when the device is running, the method for determining a splitter deployment plan of the above embodiment is executed. Figure 4 FIG. 1 is a schematic structural diagram 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 optical splitter deployment scheme determination device 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] A first prediction module 42 is configured to obtain a first number of network communication devices installed in a plurality of sub-regions within a target region within a current timestamp, and analyze the first number of devices installed in each sub-region within the current timestamp using a pre-trained first prediction model to obtain a predicted number of devices installed in each sub-region within a first time period, wherein the first time period is any time period after the current timestamp;

[0121] A first determining module 44 is configured to determine a plurality of initial deployment plans based on the predicted number of installed devices corresponding to each sub-area within the first time period and the first number of pre-deployed optical splitters in the target area;

[0122] The second prediction module 46 is configured to determine, for each initial deployment plan, a non-coverage rate of optical splitter resources in each sub-area when the optical splitter is deployed according to the initial deployment plan, and analyze the predicted number of installed devices and the non-coverage rate of optical splitter resources in each sub-area within the first time period using a pre-trained second prediction model to obtain a predicted number of work orders to be installed corresponding to each sub-area when the optical splitter is deployed according to the initial deployment plan within the first time period, wherein the non-coverage rate of optical splitter resources is a first ratio of a second number of standard addresses that are still not covered by the optical splitter after the optical splitter is deployed in the sub-area according to the initial deployment plan to a third number of standard addresses that are not covered by the operator's service in the sub-area at a 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 transferred to installation 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 program modules (for example, a set of program instructions that implement a certain specific function) or hardware modules. 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 the second embodiment of the present application, an embodiment of a device for determining a splitter deployment plan is also provided, and when the device is running, the method for determining a splitter deployment plan of the above embodiment is executed. Figure 5 FIG. 1 is a schematic structural diagram 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 optical splitter deployment scheme determination device 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 configured to obtain a first installed quantity of network communication equipment in multiple sub-regions within the target region at a current timestamp, and determine a predicted installed quantity corresponding to each sub-region within a first time period based on the first installed quantity of each sub-region at the current timestamp;

[0128] A third determining module 54 is configured to determine a plurality of initial deployment plans based on the predicted number of installed devices corresponding to each sub-area within 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 optical splitter resources when each sub-area deploys the optical splitter according to the initial deployment plan, and determine, based on the predicted number of installations in each sub-area in the first time period and the non-coverage rate of the optical splitter resources, the number of predicted work orders to be installed corresponding to each sub-area when the optical splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of the optical splitter resources is a first ratio of a second number of standard addresses that are still not covered by the optical splitter after the sub-area deploys the optical 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 at the current timestamp;

[0130] The fourth determination module 58 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 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 program modules (for example, a set of program instructions that implement a certain specific function) or hardware modules. 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. 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 plan in Example 1 and the method for determining the splitter deployment plan 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 equipment installed in multiple sub-areas within 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 the 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 number of installations and the non-coverage rate of spectrometer 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 spectrometer is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of spectrometer resources is a first ratio of the second number of standard addresses that are still not covered by the spectrometer after the sub-area pre-deploys the spectrometer 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 equipment installed in multiple sub-areas within the target area within the current timestamp, and determining a predicted installed quantity corresponding to each sub-area within the first time period based on the first installed quantity of each sub-area within 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 the first quantity of pre-deployed optical splitters within 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 determining the predicted installed quantity corresponding to each sub-area within the first time period ... The predicted number of installed devices and the non-coverage rate of the spectrometer resources are used to determine the predicted number of work orders to be transferred to installation corresponding to each sub-area when the spectrometer is deployed according to the initial deployment plan within the first time period, wherein the non-coverage rate of the spectrometer resources is a first ratio of the second number of standard addresses that are still not covered by the spectrometer after the sub-area deploys the spectrometer 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 in 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 within 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 the first quantity of pre-deployed optical splitters in the target area; for each initial deployment plan, determining the optical splitter resource coverage rate when each sub-area deploys the optical splitter according to the initial deployment plan, and using a pre-trained second prediction model to obtain the predicted installed quantity corresponding to each sub-area within the 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 equipment installed in multiple sub-areas within the target area within a current timestamp, and determining a predicted installed quantity corresponding to each sub-area within a first time period based on the first installed quantity of each sub-area within 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 the first quantity of pre-deployed optical splitters within the target area; for each initial deployment plan, determining a non-coverage rate of optical splitter resources when optical splitters are deployed in each sub-area according to the initial deployment plan, and determining a non-coverage rate of optical splitter resources when optical splitters are deployed in each sub-area according to the predicted installed quantity of each sub-area within the first time period; The method of determining the target deployment plan for each sub-area in the first time period from multiple initial deployment plans is based on the number of predicted work orders to be transferred to installation for each sub-area when the splitter is deployed according to the initial deployment plan within the first time period, and 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 within 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 within the first time period less than a first threshold. According to an embodiment of the present application, a processor is also provided, which is used to run a program, wherein the method of determining the splitter deployment plan in Example 1 and the method of 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 within 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 the 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 a pre-trained second prediction model to obtain the predicted installed quantity corresponding to each sub-area within the first time period; The measurement 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.

[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 within the target area within the current timestamp, and determining a predicted installed quantity corresponding to each sub-area within the first time period based on the first installed quantity of each sub-area within 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 the first quantity of pre-deployed optical splitters within 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 non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the initial deployment plan, and determining a non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the predicted installed quantity of each sub-area within the first time period and the splitter resource non-coverage rate to 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 splitter resource non-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 for all sub-areas in the target area in the first time period less than a first threshold.

[0141] According to an embodiment of the present application, an electronic device is further provided, wherein: Figure 6 is a schematic structural diagram 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, which, when executed by the one or more processors, enables the one or more processors to run the programs, wherein the programs are configured to execute the method for determining the spectrometer deployment scheme in the above-mentioned embodiment 1 and the method for determining the spectrometer 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 within 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 the 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 first prediction model to obtain the predicted installed quantity corresponding to each sub-area within the first time period; The trained second 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.

[0143] Optionally, the processor is configured to implement the following steps by executing a computer program: obtaining a first installed quantity of network communication equipment installed in multiple sub-areas within the target area within a current timestamp, and determining a predicted installed quantity corresponding to each sub-area within a first time period based on the first installed quantity of each sub-area within 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 the first quantity of pre-deployed optical splitters within 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 non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to the initial deployment plan, and determining a non-coverage rate of optical splitter resources when each sub-area deploys optical splitters according to 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 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 in the first time period less than a first threshold.

[0144] The serial numbers of the above 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 focus. 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 exemplary. For example, the division of units can be a logical function division. In actual implementation, there may be other division methods, such as 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] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected to achieve the purpose of the present embodiment according to actual needs.

[0148] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or 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 is essentially 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, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0150] The above is only a preferred embodiment 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 first installed quantities of network communication devices in multiple sub-areas within a target area within a current timestamp, and analyzing the first installed quantities of each sub-area within the current timestamp using a pre-trained first prediction model to obtain predicted installed quantities corresponding to each sub-area within a first time period, where the first time period is any time period after the current timestamp; Determining a plurality of initial deployment plans according to the predicted number of installed devices corresponding to each of the sub-areas within 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 spectrometer resources when each of the sub-areas deploys the spectrometer 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 spectrometer 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 spectrometer is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of the spectrometer resources is a first ratio of the second number of standard addresses that are still not covered by the spectrometer after the sub-area deploys the spectrometer according to the initial deployment plan to the third number of standard addresses of the operator's business that are not covered in the sub-area at 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 transferred to installation in 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 sets of first sample data, wherein the first sample data includes: a second number of installed units in a target sub-region within the target region at a past timestamp and a third number of installed units in the target sub-region within a second time period, where 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 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.

4. The method according to claim 1, wherein Determining multiple initial deployment plans based on the predicted number of installed devices in each sub-area in a future time period and the first number 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 within the first time period to a third number of standard addresses in the sub-area that are not covered by the operator's service within the current timestamp; determining whether the third ratio is less than a preset second threshold, and determining, based on the comparison result, whether a fourth number of optical splitters to be deployed in the sub-area is zero; 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, thereby obtaining a plurality of initial deployment schemes.

5. The method according to claim 1, wherein Determining the optical splitter resource coverage ratio when the optical splitter is deployed in each sub-area 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 optical splitter; For each of the sub-areas, determine the sixth number of standard addresses in the sub-area that are not covered by the splitter 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 in the sub-area that are not covered by the operator's business within 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 sets of second sample data, wherein the second sample data includes: the number of installations and the non-coverage rate of optical splitter resources in a target sub-area within the target area in a past timestamp, and the number of transferred work orders for installation in the target sub-area within a 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; Constructing a second neural network model, wherein the second neural network model includes at least: 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 optical splitter resource coverage rate of each sub-area in the first time period using the pre-trained second prediction model, the method further includes: Determine the average value and standard deviation of the installed capacity of all sub-areas in the target area during the first time period; The predicted installed capacity of each sub-region within the first time period is standardized using the average value and the standard deviation value.

8. A method for determining a splitter deployment plan, characterized in that: include: Obtaining first installed quantities of network communication devices in multiple sub-areas within the target area within a current timestamp, and determining predicted installed quantities corresponding to each sub-area within a first time period based on the first installed quantities of each sub-area within the current timestamp; Determining a plurality of initial deployment plans according to the predicted number of installed devices corresponding to each of the sub-areas within 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 optical splitter resources when each of the sub-areas deploys the optical splitter 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 optical splitter is deployed according to the initial deployment plan in the first time period based on the predicted number of installations and the non-coverage rate of the optical splitter resources of each sub-area in the first time period, wherein the non-coverage rate of the optical splitter resources is a first ratio of a second number of standard addresses that are still not covered by the optical splitter after the sub-area deploys the optical 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 at 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 transferred to installation 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 configured to obtain a first installed quantity of network communication equipment in multiple sub-areas within a 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 determining module is configured to determine a plurality of initial deployment plans according to the predicted number of installed devices corresponding to each sub-area within 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 optical splitter resources when each of the sub-areas deploys the optical splitter according to the initial deployment plan, and use a pre-trained second prediction model to analyze the predicted installed quantity and the non-coverage rate of optical splitter resources of 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 optical splitter is deployed according to the initial deployment plan in the first time period, wherein the non-coverage rate of optical splitter resources is a first ratio of a second number of standard addresses that are still not covered by the optical splitter after the sub-area deploys the optical splitter according to the initial deployment plan to a third number of standard addresses of the sub-area that are not covered by the operator's business at the current timestamp; The second determination module is used to determine a 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.

10. A device for determining a splitter deployment plan, characterized in that: include: a third prediction module, configured to obtain a first installed quantity of network communication equipment in a plurality of sub-areas within the target area within a current timestamp, and determine a predicted installed quantity corresponding to each sub-area within a first time period based on the first installed quantity of each sub-area within the current timestamp; A third determining module is configured to determine a plurality of initial deployment plans according to the predicted number of installed devices corresponding to each sub-area within 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, a non-coverage rate of optical splitter resources in each of the sub-areas when the optical splitter is deployed according to the initial deployment plan, and determine, based on the predicted number of installations and the non-coverage rate of optical splitter resources in each of the sub-areas in the first time period, the predicted number of work orders to be transferred to be installed when the optical splitter is deployed according to the initial deployment plan in each sub-area in the first time period, wherein the non-coverage rate of optical splitter resources is a first ratio of a second number of standard addresses that are still not covered by the optical splitter after the sub-area deploys the optical splitter according to the initial deployment plan to a third number of standard addresses of the operator's business that are not covered in the sub-area at 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 within 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 the optical splitter deployment plan 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 configured to run a program stored in the memory, wherein the method for determining an optical splitter deployment scheme according to any one of claims 1 to 8 is executed when the program is run.

Images