Network construction scheme generation method and device, program product, and electronic device

Abstract

The present disclosure relates to the technical field of computer, and provides a network construction scheme generation method and device, a program product and an electronic device. The method comprises: predicting a first number of new users of each residence according to regional data of a target region and network user data of each residence; determining a second number of new users of each machine room of the target region based on the first number of new users of each residence; determining an allocated user number of a single existing passive optical network device interface of each machine room based on the second number of new users, an existing user number and a first number of existing passive optical network device interfaces; obtaining a number of passive optical network device interfaces that need to be newly built for each machine room based on a relationship between the allocated user number of the machine room and a preset threshold of the machine room; and generating a network construction scheme according to the number of new users of each machine room and the number of newly built passive optical network device interfaces of each machine room. The present disclosure can improve the accuracy of the generated network construction scheme.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of computer, and in particular, to a network construction scheme generation method, a network construction scheme generation apparatus, a computer program product and an electronic device. BACKGROUND

[0002] When a communication operator makes network investment, the communication operator can predict the scale of network investment according to the development of users to avoid unreasonable allocation of network resources.

[0003] In the related art, the number of newly added users in the last month is taken as the future user increment to determine the network construction scheme. However, since the situation of each month is not the same, taking the number of newly added users in the last month as the future user increment leads to a large deviation between the predicted user increment and the actual user development, and further leads to an inaccurate generated network construction scheme.

[0004] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present disclosure, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] The purpose of the present disclosure is to provide a network construction scheme generation method and apparatus, a computer program product and an electronic device, and to at least partially improve the accuracy of the generated network construction scheme.

[0006] Other characteristics and advantages of the present disclosure will become apparent from the following detailed description, or will be learned by practice of the present disclosure.

[0007] According to a first aspect of the present disclosure, a network construction scheme generation method is provided, comprising: predicting a first number of newly added users of each residence according to regional data of a target region and network user data of each residence of the target region; determining a second number of newly added users of each machine room of the target region based on the first number of newly added users of each residence; determining an allocated user number of a single existing passive optical network device interface of each machine room based on the second number of newly added users of each machine room, an existing user number of each machine room, and a first number of existing passive optical network device interfaces of each machine room; for each machine room, obtaining a number of passive optical network device interfaces that need to be newly built in the machine room based on a relationship between the allocated user number of the single existing passive optical network device interface of the machine room and a preset threshold value of the machine room; and generating a network construction scheme of the target region according to the second number of newly added users of each machine room and the number of newly built passive optical network device interfaces of each machine room.

[0008] According to a second aspect of the present disclosure, a network construction scheme generation apparatus is provided, comprising: a prediction module configured to predict a first number of new users of each residential area according to regional data of a target area and network user data of each residence of the target area; a second new user number determination module configured to determine a second number of new users of each machine room of the target area based on the first number of new users of each residence; a single interface allocation user number determination module configured to determine an allocation user number of a single existing passive optical network equipment interface of each machine room based on the second number of new users of each machine room, an existing user number of each machine room, and a first number of existing passive optical network equipment interfaces of each machine room; a newly-built interface number determination module configured to obtain a number of newly-built passive optical network equipment interfaces of each machine room based on a relationship between the allocation user number of the single existing passive optical network equipment interface of the machine room and a preset threshold of the machine room; and a network construction scheme generation module configured to generate a network construction scheme of the target area according to the number of new users of each machine room and the number of newly-built passive optical network equipment interfaces of each machine room.

[0009] According to a third aspect of the present disclosure, a computer program product containing instructions, which, when executed on a computer, cause the computer to perform the steps of the network construction scheme generation method according to the first aspect.

[0010] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, which stores a computer program, and the program, when executed by a processor, implements the network construction scheme generation method according to the first aspect of the above-mentioned embodiments.

[0011] According to a fifth aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a storage device configured to store one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the network construction scheme generation method according to the first aspect of the above-mentioned embodiments.

[0012] According to the above technical solutions, the network construction scheme generation method, the network construction scheme generation apparatus, and the computer program product and the electronic device for implementing the network construction scheme generation method according to the exemplary embodiments of the present disclosure have at least the following advantages and positive effects:

[0013] In the technical solution provided by some embodiments of the present disclosure, the first number of new users of each residence can be predicted according to the regional data of the target region and the network user data of each residence, the first number of new users of each residence is aggregated to obtain the second number of new users of the machine room, then the number of users of the single passive optical network device interface of the machine room is determined according to the second number of new users of the machine room, the number of passive optical network device interfaces that need to be newly built of the machine room is obtained according to the relationship between the number of users of the single passive optical network device interface and the preset threshold, and thus the network construction scheme of the target region is generated. Compared with the prior art, on the one hand, the present disclosure can perform user increment prediction according to multi-dimensional and multi-source data by means of regional data and network user data, thereby improving the accuracy of user increment prediction and further assisting in improving the accuracy of the generated network construction scheme; on the other hand, the present disclosure obtains the number of passive optical network device interfaces that need to be newly built according to the relationship between the number of users of the single passive optical network device interface of the machine room and the threshold, and thus the number of newly built passive optical network devices can be reasonably given while ensuring the quality of network service, thereby avoiding waste of passive optical network device resources.

[0014] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0015] The accompanying drawings, which are incorporated into and form part of the specification, illustrate an embodiment consistent with the present disclosure and, together with the specification, serve to explain the principles of the present disclosure. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0016] Figure 1 A schematic diagram of an exemplary system architecture to which embodiments of the present disclosure can be applied is shown;

[0017] Figure 2 A flowchart of a network construction scheme generation method in an exemplary embodiment of the present disclosure is shown;

[0018] Figure 3 A flowchart of a method for determining the second number of new users in an exemplary embodiment of the present disclosure is shown;

[0019] Figure 4 A flowchart of a method for obtaining the number of passive optical network device interfaces that need to be newly built of each machine room in an exemplary embodiment of the present disclosure is shown;

[0020] Figure 5 A structural diagram of a gigabit network construction scheme generation system in an exemplary embodiment of the present disclosure is shown.

[0021] Figure 6 Fig. 1 shows a flow chart of a method for determining the number of new passive optical network devices according to an example embodiment of the present disclosure;

[0022] Figure 7 Fig. 2 shows a schematic diagram of a graphical user interface according to an example embodiment of the present disclosure;

[0023] Figure 8 Fig. 3 shows a schematic diagram of another graphical user interface according to an example embodiment of the present disclosure;

[0024] Figure 9 Fig. 4 shows a schematic diagram of a network construction scheme generation device according to an example embodiment of the present disclosure;

[0025] Figure 10 Fig. 5 shows a schematic diagram of an electronic device according to an example embodiment of the present disclosure. DETAILED DESCRIPTION

[0026] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations can be implemented in any

[0027] The terms "one", "a", "an", and "the" as used herein mean "at least one" or "one or more" unless expressly specified otherwise. The term "plurality" as used herein means "two or more" unless expressly specified otherwise. The term "exemplary" as used herein means "serving as an example, instance, or illustration," and not "preferred" or "advantageous over other examples." As used herein, the term "or" is

[0028] In addition, the accompanying drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0029] When telecommunications operators invest in and build networks, they can calculate the scale of investment based on user development before formal construction begins, thereby avoiding irrational allocation of network resources.

[0030] Related technologies often use the previous month's user growth data as a proxy for projected user growth when estimating network investment scale. Because user growth rates vary over time, this method can significantly deviate from actual user growth, leading to lower accuracy in the resulting network investment and construction plans. Furthermore, related technologies require manual reporting from lower-level organizations for investment and capacity expansion, resulting in multiple gaps and manual involvement in planning, design, feasibility studies, and plan generation. This approach, however, lacks intelligence and leads to inefficient network construction.

[0031] In order to solve the above problems, the present invention provides a method and device for generating a network construction plan, which can be applied to Figure 1 In the system architecture of the exemplary application environment shown.

[0032] like Figure 1 As shown, system architecture 100 may include a terminal device 110 and a server 120. Terminal device 110 may be a smartphone, tablet computer, desktop computer, laptop computer, smart wearable device, or other terminal device. Server 120 generally refers to a backend system that provides services related to the network construction plan generation method in this exemplary embodiment and may be a single server or a cluster of multiple servers. Terminal 110 and server 120 may be connected via a wired or wireless communication link to exchange data.

[0033] In an exemplary embodiment, the network construction scheme generation method described above can be executed by the terminal device 110. Correspondingly, a network construction scheme generation apparatus can be arranged in the terminal 110 to realize the corresponding module functions. For example, a user can input the region identifier of the target region for which network construction is needed in the terminal device 110, and the terminal device 110 can acquire the region data and the network user data of the region according to the region identifier, and then predict the first number of new users of each residence, and then obtain the second number of new users of each machine room according to the first number of new users of each residence, and then obtain the number of users of the single passive optical network device interface of each machine room according to the second number of new users, so as to obtain the number of passive optical network devices that need to be newly built according to the relationship between the number of users of the single passive optical network device interface and the threshold value, so as to generate the network construction scheme of the region.

[0034] In an exemplary embodiment, the network construction scheme generation method described above can be executed by the server 120. Correspondingly, a network construction scheme generation apparatus can be arranged in the server 120 to realize the corresponding module functions. For example, a user can input the region identifier of the target region for which network construction is needed in the terminal device 110, and the terminal device 110 can send the region identifier to the server 120, and the server 120 can acquire the region data and the network user data of the region according to the region identifier, and then predict the first number of new users of each residence, and then obtain the second number of new users of each machine room according to the first number of new users of each residence, and then obtain the number of users of the single passive optical network device interface of each machine room according to the second number of new users, so as to obtain the number of passive optical network devices that need to be newly built according to the relationship between the number of users of the single passive optical network device interface and the threshold value, so as to generate the network construction scheme of the region, and return the generated network construction scheme to the terminal device 110, so as to display the generated network construction scheme in the terminal device 110.

[0035] It should be understood that Figure 1 The number of terminal devices and servers in the above description is only illustrative. According to the needs of implementation, there can be any number of terminal devices and servers. For example, the server 120 can be a stand-alone physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, and basic cloud computing services such as big data and artificial intelligence platforms.

[0036] Figure 2 A flowchart of a network construction scheme generation method in an exemplary embodiment of the present disclosure is shown. Referring to Figure 2 , the method comprises:

[0037] Step S210 , predicting the first number of newly added users in each residence based on the regional data of the target area and the network user data of each residence in the target area;

[0038] Step S220, determining a second number of new users in each computer room in the target area based on the first number of new users in each residence;

[0039] Step S230, determining the number of allocated users for a single existing passive optical network device interface in each computer room based on the second number of newly added users in each computer room, the number of existing users in each computer room, and the first number of existing passive optical network device interfaces in each computer room;

[0040] Step S240: for each computer room, based on the relationship between the number of allocated users of the single existing passive optical network device interface in the computer room and a preset threshold of the computer room, obtaining the number of new passive optical network device interfaces that need to be added to the computer room;

[0041] Step S250: generating a network construction plan for the target area according to the second number of newly added users in each computer room and the number of newly built passive optical network device interfaces in each computer room.

[0042] exist Figure 2 In the technical solution provided by the illustrated embodiment, a first number of new users for each residence can be predicted based on the regional data of the target area and the network user data of each residence. The first number of new users for each residence is aggregated to obtain a second number of new users for the computer room. The number of users per single passive optical network device interface in the computer room is then determined based on the second number of new users in the computer room. Based on the relationship between the number of users per single passive optical network device interface and a preset threshold, the number of new passive optical network device interfaces required for the computer room is determined, thereby generating a network construction plan for the target area. Compared with the prior art, on the one hand, the present disclosure, through regional data and network user data, can predict user increments based on multi-dimensional and multi-source data, thereby improving the accuracy of user increment predictions and thereby assisting in improving the accuracy of the generated network construction plan. On the other hand, based on the relationship between the number of users per single passive optical network device interface in the computer room and a threshold value, the present disclosure can determine the number of new passive optical network device interfaces required to be built. This can provide a reasonable number of new passive optical network devices while ensuring network service quality, thereby avoiding waste of passive optical network device resources.

[0043] The following Figure 2 The specific implementation of each step in the embodiment shown is described in detail:

[0044] Next, the specific implementation of "step S210, predicting the first number of new users of each residence according to the regional data of the target region and the network user data of each residence in the target region" will be described in detail.

[0045] In an exemplary embodiment, the target region can be determined according to demand, and the target region can be a specific geographic region, such as A city or A city B county, etc. The residences in the target region can include residential communities in the target region that have been built and / or residential communities in the target region that are being built. In other words, the present disclosure can predict the number of new users in a community as a granularity. Taking a gigabit network as an example, the first number of new users can be understood as the predicted number of new users of the gigabit network in a certain community.

[0046] In an exemplary embodiment, the regional data of the target region includes one or more of the network coverage data of the target region and the development potential score of the target region; the network user data of each residence includes one or more of the number of households in the residence, whether the residence is a newly built residence, the historical number of new users of the residence, the number of users in the residence who have migrated to the network, the number of users in the residence who have migrated out of the network, the number of users in the residence who have removed network signal receiving equipment, and the consumption capacity of the users in the residence to the network.

[0047] Taking A city B county as an example, the number of households in each community in B county, the proportion of different operator networks in the community, the number of users in the community who use high-value network products of the operator, the number of new users of the operator network in the community in the last month or the last N months, the number of users who have removed the device in the community, the number of users who have migrated in or out of the network in the community, the satisfaction of users in the community to the network, etc. Community user data can be obtained from the operator's information platform, whether the community is a newly built community can be obtained from the developer's marketing platform, and a new building label can be added to the community. The community label is also one of the network user data. The development potential evaluation score of B county and the 5G network coverage of B county can be determined according to the data in the operator's information platform, so as to obtain multi-source, multi-dimensional data to predict the future number of users in the community.

[0048] In an exemplary embodiment, the network of the present disclosure can include a gigabit network, i.e. when performing gigabit network construction estimation, the number of new users of the gigabit network can be predicted according to the regional data of the region and the multi-source, multi-dimensional data related to the user. In other words, the first number of new users in step S210 can include the first number of new gigabit network users, i.e. the number of users using the gigabit network in each residential community.

[0049] Exemplarily, a specific implementation of step S210 may include: predicting the first number of new users in each residence based on the regional data of the target area and the network user data of each residence in the target area and based on a pre-trained multi-dimensional time series neural network prediction model.

[0050] For example, regional data of different areas at different times and network user data of each residence in each area during that time can be obtained as training data. The number of users of each residence during that time can be used as a label to train a multi-dimensional time series neural network prediction model to perform residential user increment prediction, thereby obtaining a pre-trained multi-dimensional time series neural network prediction model.

[0051] In an exemplary embodiment, the multidimensional time series neural network model in the present disclosure may include a sarima (Seasonal Autoregressive Integrated Moving Average) model. The process of constructing a sarima model may include a data exploration stage, a parameter selection stage, a model fitting stage, and a model diagnosis stage. The data exploration stage mainly checks whether the time series shows a trend and / or seasonal pattern. The parameter selection stage determines the values ​​of p, d, q and P, D, Q in the model based on the autocorrelation function (ACF) and partial autocorrelation function (PACF) graphs of the time series. The model fitting stage can use the selected parameters to fit the sarima model. The model diagnosis stage can verify the validity of the model through residual analysis and other means. After the validity of the model is verified, a pre-trained multidimensional time series neural network model can be obtained, and the model can be used to predict future time points.

[0052] Some time series exhibit significant cyclical variations. These cycles are caused by seasonal variations (e.g., quarterly, monthly, or weekly) or other inherent factors, such as weather and holidays. These series are called seasonal series. The sarima model supports time series data with seasonal components. The model parameters p represent the order of the non-seasonal autoregression, q represents the order of the non-seasonal moving average, d represents the number of one-step differencing, P represents the order of the seasonal autoregression, Q represents the order of the seasonal moving average, and D represents the number of seasonal differencing.

[0053] Taking the construction of a gigabit network as an example, after obtaining a pre-trained sarima model through training data, for any residence in any target area, the regional data of the target area and the gigabit network user data of the residence can be input into the sarima model. Based on the output of the sarima model, the number of new gigabit network users in the residence in the future can be predicted, that is, the number of new gigabit network users that can be added based on the above-mentioned first number of new users.

[0054] Currently, the network in the present disclosure can also be other types of networks, such as a gigabit network, a 5G network, etc., and the present exemplary embodiment does not make special limitations thereon. When the network is a gigabit network, the first number of newly added users is the number of newly added gigabit network users.

[0055] It should be noted that the number of newly added users in the present disclosure can also be predicted by other multi-dimensional time sequence neural network models, such as an autoregressive integrated moving average model, etc., and the present exemplary embodiment does not make special limitations thereon.

[0056] Next, the specific implementation of "step S220, determining the second number of newly added users of each machine room in the target area based on the first number of newly added users of each residence" will be described in detail.

[0057] For example, after obtaining the first number of newly added users of each residence in the target area, the second number of newly added users of each machine room in the target area can be obtained according to the relationship between each residence and the machine room. The second number of newly added users can be understood as the total number of users who need to provide network services in the future and are newly added to each machine room.

[0058] Exemplarily, Figure 3 A flowchart of a method for determining the second number of newly added users in an exemplary embodiment of the present disclosure is shown. Referring to Figure 3 The method can include steps S310 to S340.

[0059] Among them:

[0060] In step S310, in the case where a residence is associated with a machine room, the machine room associated with the residence is determined as the target machine room of the residence.

[0061] Taking a gigabit network as an example, in the case where a passive optical network residential area is associated with one machine room, the machine room is the target machine room of the residential area.

[0062] In step S320, in the case where a residence is associated with multiple machine rooms, the machine room with the largest number of idle passive optical network device interfaces among the multiple machine rooms is determined as the target machine room of the residence.

[0063] Continuing to take the gigabit network as an example, in the case where a passive optical network residential area is associated with multiple machine rooms, the machine room with the largest number of idle gigabit users can be selected from the multiple uplink OLT (Optical Line Terminal, optical line terminal, terminal device for connecting fiber trunk) machine rooms as the target machine room of the residential area.

[0064] In step S320, the target associated residence of each machine room is determined according to the target machine room of each residence.

[0065] For example, the target associated residences of each machine room can be determined by aggregating the residences of the same target machine room according to the target machine room of each residence, i.e., obtaining the target associated residences of each machine room.

[0066] In step S330, the second number of newly added users of each machine room is determined according to the sum of the first number of newly added users of the target associated residences of each machine room.

[0067] For example, after obtaining the target associated residences of each machine room, the number of newly added gigabit network users of the target associated residences corresponding to each machine room can be summarized to obtain the number of newly added gigabit network users of each machine room, i.e., the second number of newly added users.

[0068] Next, the specific implementation of "step S230, determining the number of distributed users of a single existing passive optical network device interface of each machine room based on the second number of newly added users of each machine room, the number of existing users of each machine room, and the first number of existing passive optical network device interfaces of each machine room" is described in detail.

[0069] In an exemplary embodiment, the passive optical network device interface can be understood as a PON (Passive Optical Network) interface. The PON interface can include one or more of a GPON (Gigabit Passive Optical Network) and an EPON (Ethernet Passive Optical Network) interface.

[0070] For example, one specific implementation of step S230 can include: determining the number of to-be-distributed users of each machine room based on the sum of the second number of newly added users of each machine room and the number of existing users of each machine room; and determining the number of distributed users of a single existing passive optical network device interface of each machine room according to the quotient of the number of to-be-distributed users of each machine room and the first number of existing passive optical network device interfaces of each machine room.

[0071] In an exemplary embodiment, the existing passive optical network device interface of a machine room can be understood as the existing passive optical network device interface of each machine room, which can include the passive optical network device interface being used in the machine room and the idle passive optical network device interface in the machine room. That is, the first number of existing passive optical network interfaces of a machine room is the sum of the number of used passive optical network device interfaces in the machine room and the number of idle passive optical network device interfaces in the machine room.

[0072] For example, the total number of users to be served in the future of each machine room can be obtained according to the sum of the second number of newly added users in each machine room and the original number of users in each machine room, and then the number of users allocated to each PON interface in the existing PON interface of each machine room is obtained by dividing the total number of users to be served in the future of each machine room by the first number of existing PON device interfaces of each machine room, that is, the number of users carried by a single PON interface in each machine room.

[0073] Next, the specific implementation of "step S240, obtaining the number of newly built PON device interfaces of each machine room based on the relationship between the number of users allocated to the single existing PON device interface of the machine room and the preset threshold value of the machine room" will be described in detail.

[0074] In an exemplary embodiment, the preset threshold value is used to represent the maximum number of users that can be accessed by a single PON device interface of the machine room. For example, the preset threshold value can be understood as a single PON port gigabit user number threshold value.

[0075] For example, the preset threshold values of machine rooms in different regions can be pre-configured, and the preset threshold values can be determined according to needs and experience. For example, the preset threshold value of a machine room in a densely populated area can be set to be larger, and the preset threshold value of a machine room in a sparsely populated area can be set to be smaller. For example, the preset threshold value of a machine room in a main city area can be 3.5, the preset threshold value of a machine room in a suburb area can be 2, and the preset threshold value of a machine room in a county area can be 1.5. For example, a machine room in a main city area is managed by a branch company, the single PON port gigabit user number threshold value of the machine room of the branch company is 3.5, the single PON port gigabit user number threshold value of a machine room of a first type branch company is 2.8, the single PON port gigabit user number threshold value of a machine room of a second type branch company is 2, and the single PON port gigabit user number threshold value of a machine room of a third type branch company is 1.5. The specific level and value of the division can be determined according to needs and experience, and the present exemplary embodiment does not make special limitations.

[0076] Based on this, the exemplary embodiment of the present disclosure is as follows. Figure 4 A flowchart of a method for obtaining the number of newly built PON device interfaces of each machine room in an exemplary embodiment of the present disclosure is shown. Referring to FIG. 4, Figure 4 The method can include steps S410 to S430. Wherein:

[0077] In step S410, the number of newly added PON device interfaces of the machine room is obtained based on the relationship between the number of users allocated to the single existing PON device interface of the machine room and the preset threshold value of the machine room.

[0078] For example, in one embodiment of step S410, if the number of users allocated to the single existing PON interface of the machine room is greater than the preset threshold, the number of newly added PON interfaces of the machine room is obtained according to the quotient between the second number of newly added users of the machine room and the preset threshold.

[0079] For example, when the number of users allocated to the single PON interface of the machine room is greater than the preset threshold, it indicates that the number of newly added users of the machine room will make the number of users carried by the existing PON interface of the machine room greater than the threshold, i.e., the existing PON device cannot simultaneously support the newly added users and the original users, so it is necessary to add a PON interface in the machine room. The number of PON interfaces that need to be added in the machine room can be obtained according to the following formula (1):

[0080]

[0081] For example, in another embodiment of step S410, if the number of users allocated to the single existing PON interface of the machine room is less than the preset threshold, it is determined that the machine room does not need to add a PON interface.

[0082] For example, when the number of users allocated to the single existing PON interface of the machine room is less than the preset threshold, it indicates that the existing PON device of the machine room can support the newly added users and the original users, so it is not necessary to add a PON device in the machine room, i.e., the number of newly added PON interfaces of the machine room is 0.

[0083] In one example embodiment, the number of PON interfaces that need to be added in each machine room is obtained in step S410. Considering the case of reusing, the number of idle PON interfaces in each machine room can be subtracted from the above value to obtain the actual demand for PON interfaces in each machine room.

[0084] In step S420, idle PON devices of the target area are obtained, and the idle PON devices of the target area are allocated to each machine room of the target area according to a preset rule.

[0085] For example, the number of idle PON devices in the PON board management unit of the target area can be obtained, and then the idle PON devices are allocated to each machine room of the target area according to a preset rule, so as to realize the reuse of PON devices and avoid the waste of PON device resources.

[0086] In an exemplary embodiment, the preset rule can comprise sorting the machine rooms according to the ascending order of the actual PON port demand of each machine room, and then according to the sorting result, preferentially allocating the idle PON equipment to the machine room with less actual demand for PON equipment. In this way, some machine rooms can be completely expanded according to the old PON board, which is convenient for subsequent troubleshooting and positioning, and also makes the demand for board cards in each machine room more concentrated, which is convenient for subsequent construction when expanding the machine room.

[0087] In another exemplary embodiment, the preset rule can also comprise sorting each machine room according to the descending order of the actual PON port demand of each machine room, and then according to the sorting result, preferentially allocating the idle PON board to the machine room with large actual demand for PON port. In this way, the timeliness of PON board supply for machine rooms with large demand can be ensured, thereby preferentially meeting the demand of more users.

[0088] In another exemplary embodiment, the preset rule can comprise the distance between each machine room and the unit of the management PON board of the target area for the allocation of idle PON board, such as preferentially allocating idle PON board to the machine room close to the unit of the management PON board, thereby saving the transportation cost in subsequent network construction.

[0089] In step S430, the number of PON equipment interfaces that need to be newly built in the machine room is obtained according to the difference between the number of PON equipment interfaces newly added in the machine room and the number of PON equipment interfaces provided by the idle PON equipment allocated to the machine room.

[0090] For example, for each machine room, the actual PON port demand of the machine room calculated in step S410 is subtracted from the number of old PON interfaces provided by the idle PON board allocated from the management unit, to obtain the number of PON interfaces that the machine room really needs to be newly built.

[0091] That is, since there may be idle PON equipment in the PON equipment management unit of the target area (such as each regional branch), the number of PON equipment that each machine room really needs to be newly built can be obtained according to the actual PON port demand of each machine room and the number of idle PON equipment that can be allocated. For example, the actual PON port demand of the machine room is 100, the number of idle PON equipment allocated is 5, and each PON equipment can provide 8 PON ports. That is, 60 PON ports still need to be newly built, and if each newly built PON equipment can provide 8 PON ports, the number of PON equipment that needs to be newly built is 60 divided by 8 rounded up, that is, 8.

[0092] Through the steps S410 to S430, the idle PON board cards can be allocated to each machine room according to the actual number of PON interfaces to be newly added in each machine room, and the number of PON board cards to be newly built in each machine room is obtained, so as to realize the reuse of PON board cards and avoid the waste of PON board cards.

[0093] Next, the implementation of the step S250, generating the network construction scheme of the target area according to the second number of newly added users in each machine room and the number of newly built passive optical network equipment interfaces in each machine room, will be described in detail.

[0094] For example, one specific implementation of the step S250 can include: inputting the number of newly added users in each machine room, the number of newly built passive optical network equipment interfaces in each machine room, and the number of idle passive optical network equipment allocated to each machine room into a large language model, and generating the network construction scheme of the target area according to the output of the large language model.

[0095] For example, the information such as the name of the target area, the predicted number of newly added users in the target area (i.e. the sum of the first number of newly added users in each residence), the number of newly added users in each machine room, the total number of idle PON board cards allocated, the number of idle PON board cards allocated to each machine room, the number of PON board cards to be newly built in each machine room, the type of PON board cards to be newly built in each machine room, etc. can be input into the large language model, and the large language model can integrate these information according to the preset content generation version, so as to generate the network construction scheme of the target area.

[0096] For example, Figure 5 The structure schematic diagram of a gigabit network construction scheme generation system in an exemplary embodiment of the present disclosure is shown. Referring to Figure 5 The system can include a user growth prediction module 51, a PON board card calculation module 52, and a large model construction scheme generation module 53.

[0097] For example, the user growth prediction module 51 can combine the residential community basic data of the target area, the community data label (whether it is a newly built community label), the relationship between the community and the machine room, the relationship between the machine room and the target area, and other data to filter, sort and eliminate outliers, train the user growth time series prediction model, and predict the number of all gigabit network users under all single machine rooms of the network operator in the target area based on the multi-dimensional time series neural network prediction algorithm. For example, the cell population of the residential community in the target area, the number of newly added gigabit network users last month, whether the community is newly built, the proportion of users consuming high-value network products in the community, the broadband penetration rate (i.e., the proportion of network users of different operators), the number of disassembled users, the regional development potential score, and other multi-dimensional data can be input into the time series prediction model. Through model reasoning and algorithm verification, the time series prediction model can obtain the predicted gigabit user increment of each residential community, aggregate the gigabit user increment of each residential community at the machine room level, and obtain the predicted gigabit user increment of each machine room.

[0098] The PON board card calculation module 52 can predict the number of PON board cards that should be newly built and can be recycled in each machine room according to the types of board cards in each machine room, idle board cards, idle ports, preset thresholds, the predicted gigabit user increment of each machine room, and the number of original gigabit users in each machine room.

[0099] The data calculated by the user growth prediction module 51 and the PON board card calculation module 52 can be integrated according to a certain output template to obtain prompt words corresponding to different questions, and the prompt words can be input into the large model to generate a construction scheme 53 to obtain a network construction scheme through the output of the large language model.

[0100] Next, reference will be made to Figure 6 The implementation of the PON board card calculation module 52 predicting the number of PON board cards that should be newly built and can be recycled in each machine room will be further described. For example, Figure 6 A flowchart of a method for determining the number of newly built passive optical network devices in an exemplary embodiment of the present disclosure is shown, and reference is made to Figure 6 The method can include steps S601 to S615. Wherein:

[0101] In step S601, the predicted residential area gigabit user growth quantity of the target area is acquired; in step S602, the residential area gigabit user growth quantity is summarized to the gigabit user growth quantity of a single machine room; in step S603, the newly added PON interface quantity of the machine room dimension is generated; in step S604, the idle quantity of the existing PON interface of the machine room is acquired, and the actual PON port demand quantity of the machine room is obtained according to the difference between the newly added PON interface quantity and the idle quantity of the machine room; if the actual PON port demand quantity is less than or equal to 0, the step S605 is transferred to, otherwise, the step S606 is transferred to; in step S605, it is determined that the machine room does not need to be expanded; in step S606, the machine room is expanded according to the idle PON board card; in the case where the idle PON board card quantity in the same branch company is greater than or equal to the actual PON board card demand quantity, the step S607 can be transferred to, otherwise, the step 608 is transferred to; in step S607, the idle PON board card is called to expand the machine room; in step S608, the PON board card is newly built to expand.

[0102] For example, the newly added PON interface quantity of the machine room can be obtained according to the quotient value of the newly added user quantity and the single PON port user quantity threshold value of the machine room, and then the actual PON port demand quantity of the machine room is obtained by subtracting the idle PON port quantity of the machine room from the newly added PON port quantity of the machine room. If the actual PON port demand quantity is less than or equal to 0, the machine room can not need to be expanded, that is, the PON card quantity to be newly built by the machine room is 0. If the actual PON port demand quantity is greater than 0, the actual PON board card demand quantity can be obtained according to the actual PON port demand quantity and the PON port quantity that can be provided by a single PON board card, for example, if the actual PON port demand quantity is 50 and a single PON board card can provide 8 PON ports, the actual PON board card demand quantity is 7 by using 50 divided by 8 and rounding up. If the idle PON board card quantity in the same branch company is greater than or equal to the actual PON board card demand quantity, the idle PON board card in the same branch company can be directly called to expand the machine room. If the idle PON board card quantity in the same branch company is less than the actual PON board card demand quantity, the PON board card quantity to be newly built is obtained by subtracting the idle PON board card quantity in the same branch company from the actual PON board card demand quantity, so as to expand the machine room according to the PON board card quantity to be newly built. The PON board card quantity to be newly built is the PON board card quantity to be purchased.

[0103] When multiple machine rooms are connected to the optical network cell, the machine room with the most idle gigabit users in the uplink OLT machine room can be selected as the associated machine room of the optical network cell to perform user increment data summarization.

[0104] In the following, reference is made to Figure 7 and Figure 8An exemplary application scenario of the present disclosure is described. For example, the network construction scheme can be configured in the interface shown in Figure 7 The interface shown in FIG. 71, the user gigabit scheme scene control, the investment gigabit scheme scene control, and the like can be configured in the interface shown in Figure 7 to realize scheme prediction in different scenes. For example, in response to the triggering operation of the control of the investment gigabit scheme scene by the user, the interface shown in Figure 7 can be displayed. In the interface shown in 72, the user can input relevant data, such as branch name, whether to consider old investment, investment amount, machine room name, and the like. At the same time, the user can configure the threshold value of the number of gigabit users per 10G PON port per unit time through the parameter configuration control. After inputting the relevant information, the user can click the Figure 7 control. In response to the triggering operation of the Figure 7 control, the number of 10G PON cards required for the machine room and the number of idle 10G PON cards in the machine room can be calculated according to the information selected by the user, such as the machine room of the branch, whether to consider idle board card reuse, the input investment amount, and the configured threshold value of the number of gigabit users per 10G PON port. These information is input into the large language model, and the large language model integrates these information and outputs the construction scheme shown in Figure 8 through a fixed template. As shown in Figure 8 , the large language model can generate detailed content related to the construction scheme, such as branch name, number of gigabit users, machine room, required 10G PON type, PON number, idle port number, and number of ports to be newly built.

[0105] The present disclosure is based on multi-source and multi-dimensional data, and predicts network user growth according to a time sequence model, thereby improving the accuracy of user growth prediction and assisting in improving the accuracy of the generated construction scheme. The present disclosure calculates the newly built and old PON cards through the machine room single PON port threshold value, inputs the calculation result into the large model, and automatically generates the network construction scheme, thereby improving the generation efficiency of the construction scheme.

[0106] In addition, it should be noted that the above-mentioned figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present application, and are not for limiting purposes. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be executed synchronously or asynchronously in multiple modules, for example.

[0107] Further, the exemplary embodiments of the present disclosure also provide a network construction scheme generation device. Referring to Figure 9As shown, the network construction scheme generation apparatus 900 comprises the following program modules: a prediction module 910 configured to predict a first number of newly added users in each residential area according to regional data of a target region and network user data of each residence in the target region; a second number of newly added users determination module 920 configured to determine a second number of newly added users in each machine room of the target region based on the first number of newly added users in each residence; a single interface allocation user number determination module 930 configured to determine an allocation user number of a single existing passive optical network equipment interface in each machine room based on the second number of newly added users in each machine room, an existing user number in each machine room, and a first number of existing passive optical network equipment interfaces in each machine room; a newly built interface number determination module 940 configured to, for each machine room, obtain a number of newly built passive optical network equipment interfaces in the machine room based on a relationship between the allocation user number of the single existing passive optical network equipment interface in the machine room and a preset threshold of the machine room; and a network construction scheme generation module 950 configured to generate a network construction scheme of the target region according to the number of newly added users in each machine room and the number of newly built passive optical network equipment interfaces in each machine room.

[0108] In an exemplary embodiment, the prediction module 910 can be specifically configured to predict the first number of newly added users in each residence based on a pre-trained multi-dimensional time sequence neural network prediction model according to the regional data of the target region and the network user data of each residence in the target region; wherein the regional data of the target region comprises one or more of network coverage data of the target region and a development potential score of the target region; and the network user data of each residence comprises one or more of a number of households in the residence, whether the residence is a newly built residence, a historical number of newly added network users in the residence, a number of users in the residence who migrate into the network, a number of users in the residence who migrate out of the network, a number of users in the residence who remove network signal receiving equipment, and a consumption capacity of users in the residence.

[0109] In an exemplary embodiment, the second number of newly added users determination module 920 can be specifically configured to, in a case where the residence is associated with one machine room, determine the machine room associated with the residence as a target machine room of the residence; in a case where the residence is associated with multiple machine rooms, determine a machine room with the largest number of idle passive optical network equipment interfaces among the multiple machine rooms as the target machine room of the residence; determine target associated residences of each machine room according to the target machine room of each residence; and determine the second number of newly added users in each machine room according to a sum of the first number of newly added users in the target associated residences of each machine room.

[0110] In an exemplary embodiment, the single-interface allocation user quantity determination module 930 can be specifically configured to determine the to-be-allocated user quantity of each machine room based on the second newly-added user quantity of each machine room and the sum of the existing user quantities of each machine room; and determine the allocation user quantity of a single existing PON device interface of each machine room according to the quotient value of the to-be-allocated user quantity of each machine room and the first quantity of the existing PON device interfaces of each machine room.

[0111] In an exemplary embodiment, the preset threshold value is used to represent the maximum user quantity that can be accessed by a single PON device interface of the machine room, and based on this, the newly-added interface quantity determination module 940 can be specifically configured to obtain the newly-added quantity of PON device interfaces of the machine room based on the relationship between the allocation user quantity of the single existing PON device interface of the machine room and the preset threshold value of the machine room; obtain the idle PON devices of the target area, and allocate the idle PON devices of the target area to each machine room of the target area according to a preset rule; and obtain the quantity of newly-built PON device interfaces required by the machine room according to the difference between the newly-added quantity of PON device interfaces of the machine room and the quantity of PON device interfaces that can be provided by the idle PON devices allocated to the machine room.

[0112] In an exemplary embodiment, obtaining the newly-added quantity of PON device interfaces of the machine room based on the relationship between the allocation user quantity of the single existing PON device interface of the machine room and the preset threshold value of the machine room includes: in the case where the allocation user quantity of the single existing PON device interface of the machine room is greater than the preset threshold value, obtaining the newly-added quantity of PON device interfaces of the machine room according to the quotient value between the second newly-added user quantity of the machine room and the preset threshold value of the machine room; and in the case where the allocation user quantity of the single existing PON device interface of the machine room is less than the preset threshold value, determining the newly-added quantity of PON device interfaces of the machine room by the following manner: determining the to-be-allocated user quantity of the machine room according to the sum of the second newly-added user quantity of the machine room and the existing user quantity of the machine room; determining the PON device interface requirement quantity of the machine room based on the quotient value of the to-be-allocated user quantity and the preset threshold value of the machine room; and determining the newly-added quantity of PON device interfaces of the machine room according to the difference between the PON device interface requirement quantity of the machine room and the occupied PON device interface quantity of the machine room.

[0113] In an example implementation, the network construction scheme generation module 950 can be configured to input the second number of new users of each machine room, the number of newly-built PON device interfaces of each machine room, and the number of idle PON devices allocated to each machine room into a large language model, and generate the network construction scheme of the target region according to the output of the large language model.

[0114] The specific details of the parts of the above device have been described in detail in the method part implementation, and the undisclosed details can be referred to the implementation content of the method part, and thus will not be described again.

[0115] It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, such division is not mandatory. In fact, according to example implementations of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units embodied.

[0116] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this is not required or implied that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired result. Additionally or alternatively, certain steps can be omitted, multiple steps can be combined into one step, and / or one step can be divided into multiple steps, etc.

[0117] Example implementations of the present disclosure also provide a computer program product. The computer program product includes a computer program which, when executed by a processor, implements the network construction scheme generation method described above.

[0118] In an implementation, the computer program product can be a tangible product containing the computer program, such as a computer readable storage medium storing the computer program. The readable storage medium can be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, etc. signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory (Flash), mechanical hard disk (HDD), solid state disk (SSD), etc. For example, the computer program product can be implemented as a non-volatile storage medium storing the computer program, such as a read-only memory, a NAND flash memory, etc.

[0119] In an implementation, the computer program product can be an intangible product containing the computer program. For example, the computer program product can be implemented as a virtual digital product, such as an executable file, an installation package, etc. digital file storing the computer program.

[0120] The code of the computer program can be written in one or more programming languages. Programming languages such as C, Java, C++, Python, etc. The program code can be executed entirely on the user computing device, or partially on the user computing device, or as a standalone software package, or partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any kind of network, such as a local area network (LAN), a wide area network (WAN), etc., or can be connected to an external computing device (for example, through an Internet connection provided by an operator).

[0121] The computer program can be carried or transmitted by electronic, magnetic, optical, electromagnetic, infrared, etc. signals. The electronic device can convert the signal carrying the computer program into a digital signal, and then run the computer program. When the computer program is running on the electronic device, its code is used to make the electronic device execute (more specifically, can make the processor of the electronic device execute) the method steps of various exemplary embodiments of the present disclosure, such as the network construction scheme generation method described above, which includes the following steps: predicting the first number of new users of each residence according to the regional data of the target area and the network user data of each residence in the target area; determining the second number of new users of each machine room in the target area based on the first number of new users of each residence; determining the number of allocated users of a single existing passive optical network device interface of each machine room based on the second number of new users of each machine room, the number of existing users of each machine room, and the first number of existing passive optical network device interfaces of each machine room; for each machine room, based on the relationship between the number of allocated users of the single existing passive optical network device interface of the machine room and the preset threshold value of the machine room, obtaining the number of passive optical network device interfaces that need to be newly built in the machine room; and generating a network construction scheme for the target area according to the second number of new users of each machine room and the number of newly built passive optical network device interfaces of each machine room.

[0122] By executing the above method steps through the computer program, on the one hand, through the regional data and the network user data, the user increment prediction can be performed according to multi-dimensional and multi-source data, the accuracy of the user increment prediction is improved, and then the accuracy of the generated network construction scheme is improved; on the other hand, according to the relationship between the number of users of a single passive optical network device interface of a machine room and the threshold value, the number of passive optical network device interfaces that need to be newly built is obtained, which can give a reasonable number of newly built passive optical network devices under the condition of ensuring the quality of network service, and avoid the waste of passive optical network device resources.

[0123] An exemplary embodiment of the present disclosure also provides an electronic device, which can be the terminal device 110 or the server 120 described above. The electronic device can include a processor and a memory. The memory stores executable instructions of the processor, which can be a computer program. The processor executes the method steps of various exemplary embodiments of the present disclosure by executing the executable instructions. In addition, the electronic device can also include a display for displaying a graphical user interface.

[0124] The following will be described with reference to Figure 10 The electronic device is exemplarily illustrated in the form of a general computing device. It should be understood that Figure 10 The electronic device 1000 shown is only an example and should not limit the functions and use range of the embodiments of the present disclosure.

[0125] As Figure 10 The electronic device 1000 can include a processor 1010, a memory 1020, a bus 1030, an I / O (Input / Output) interface 1040, a network adapter 1050, and a display 1060, as shown.

[0126] The memory 1020 can include a volatile memory, such as a RAM 1021, a cache unit 1022, and a non-volatile memory, such as a ROM 1023. The memory 1020 can also include one or more program modules 1024, which include but are not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination thereof can include the implementation of a network environment. For example, the program modules 1024 can include the modules in the above-described apparatus.

[0127] The processor 1010 can include one or more processing units, such as: an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor, and / or a NPU (Neural-Network Processing Unit), etc.

[0128] The processor 1010 can be configured to execute executable instructions stored in the memory 1020, such as the network construction scheme generation method described above, which includes the following steps: predicting the first number of new users of each residence according to the regional data of the target region and the network user data of each residence in the target region; determining the second number of new users of each machine room in the target region based on the first number of new users of each residence; determining the number of distributed users of a single existing passive optical network device interface of each machine room based on the second number of new users of each machine room, the number of existing users of each machine room, and the first number of existing passive optical network device interfaces of each machine room; for each machine room, obtaining the number of new passive optical network device interfaces that need to be built based on the relationship between the number of distributed users of the single existing passive optical network device interface of the machine room and the preset threshold value of the machine room; and generating a network construction scheme for the target region according to the second number of new users of each machine room and the number of new passive optical network device interfaces of each machine room.

[0129] By implementing the above method through a computer program, on the one hand, through regional data and network user data, user increment prediction can be performed according to multi-dimensional and multi-source data, the accuracy of user increment prediction is improved, and the accuracy of the generated network construction scheme is further improved. On the other hand, according to the relationship between the number of users of a single passive optical network device interface of a machine room and the threshold value, the number of new passive optical network device interfaces that need to be built is obtained, which can give a reasonable number of new passive optical network devices under the condition of ensuring network service quality, and avoid waste of passive optical network device resources.

[0130] The bus 1030 is configured to realize the connection between different components of the electronic device 1000, and can include a data bus, an address bus, and a control bus.

[0131] The electronic device 1000 can communicate with one or more external devices 1100 (such as a keyboard, a mouse, an external controller, etc.) through the I / O interface 1040.

[0132] The electronic device 1000 can communicate with one or more networks through the network adapter 1050, such as a network adapter 1050 that can provide a mobile communication solution such as 3G / 4G / 5G, or provide a wireless communication solution such as a wireless local area network, Bluetooth, near field communication, etc. The network adapter 1050 can communicate with other modules of the electronic device 1000 through the bus 1030.

[0133] The electronic device 1000 can display a graphical user interface through the display 1060, such as displaying the interfaces shown in the above Figure 7 and Figure 8 .

[0134] Although Figure 10Other hardware and / or software modules can also be included in electronic device 1000, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc., which are not shown.

[0135] Furthermore, the above-described diagrams are merely schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended for limiting purposes. It is readily understood that the processes shown in the above-described diagrams do not indicate or limit the time sequence of the processes. In addition, it is readily understood that the processes can be executed synchronously or asynchronously, for example, in a plurality of modules.

[0136] As can be seen, the technical solutions of the present disclosure can be implemented as a method, an apparatus, a system, a computer program product, a storage medium, an electronic device, and the like. Those skilled in the art can understand that various aspects of the present disclosure can be implemented in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, which can be referred to as "circuitry", "module", or "system", respectively.

[0137] It should be understood that the present disclosure is not limited to the specific method steps or structures described above and shown in the drawings, and various modifications and changes can be made without departing from the scope of the present disclosure. Those skilled in the art, based on the specific embodiments provided by the present disclosure, will readily think of other embodiments. Therefore, the specific embodiments provided by the present disclosure are merely exemplary, and the scope and spirit of the present disclosure are indicated by the claims, and should encompass any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure, and include common knowledge or conventional technical means in the technical field of the present disclosure that are not disclosed by the present disclosure.

Claims

1. A network build plan generation method, characterized by, The method comprises the following steps: According to the regional data of the target area and the network user data of each residence in the target area, the first number of new users of each residence is predicted; Based on the first number of new users of each residence, the second number of new users of each machine room in the target area is determined; Based on the second number of new users of each machine room, the existing number of users of each machine room, and the first number of existing passive optical network device interfaces of each machine room, the distribution number of users of a single existing passive optical network device interface of each machine room is determined; For each machine room, based on the relationship between the distribution number of users of a single existing passive optical network device interface of the machine room and the preset threshold value of the machine room, the number of passive optical network device interfaces that need to be newly built in the machine room is obtained; According to the second number of new users of each machine room and the number of newly built passive optical network device interfaces of each machine room, a network construction scheme of the target area is generated.

2. The method of claim 1, wherein, The method comprises the following steps: According to the regional data of the target area and the network user data of each residence in the target area, the first number of new users of each residence is predicted based on a pre-trained multi-dimensional time sequence neural network prediction model; The regional data of the target area comprises one or more of network coverage data of the target area and development potential score of the target area; the network user data of each residence comprises one or more of the number of residents of the residence, whether the residence is a newly built residence, the historical number of new network users of the residence, the number of users moving into the network in the residence, the number of users moving out of the network in the residence, the number of users removing network signal receiving devices in the residence, and the consumption capacity of users in the residence.

3. The method of claim 1, wherein, The method comprises the following steps: In the case that the residence is associated with one machine room, the machine room associated with the residence is determined as the target machine room of the residence; In the case that the residence is associated with multiple machine rooms, the machine room with the largest number of idle passive optical network device interfaces among the multiple machine rooms is determined as the target machine room of the residence; According to the target machine room of each residence, the target associated residence of each machine room is determined; According to the sum of the first number of new users of the target associated residence of each machine room, the second number of new users of each machine room is determined.

4. The method of claim 1, wherein, The method comprises the following steps: Based on the second number of new users of each machine room and the sum of the existing number of users of each machine room, the to-be-distributed number of users of each machine room is determined; According to the quotient value of the to-be-distributed number of users of each machine room and the first number of existing passive optical network device interfaces of each machine room, the distribution number of users of a single existing passive optical network device interface of each machine room is determined.

5. The method of claim 1, wherein, The preset threshold value is used to represent the maximum number of users that can be accessed by a single passive optical network device interface of the machine room. The number of passive optical network device interfaces that need to be newly built in the machine room is obtained based on the relationship between the number of allocated users of the single existing passive optical network device interface of the machine room and the preset threshold value of the machine room, and includes: The number of passive optical network device interfaces that need to be newly built in the machine room is obtained based on the relationship between the number of allocated users of the single existing passive optical network device interface of the machine room and the preset threshold value of the machine room. Idle passive optical network devices in the target area are obtained, and the idle passive optical network devices in the target area are allocated to each machine room in the target area according to a preset rule. The number of passive optical network device interfaces that need to be newly built in the machine room is obtained according to the difference between the number of newly added passive optical network device interfaces of the machine room and the number of passive optical network device interfaces that can be provided by the idle passive optical network devices allocated to the machine room.

6. The method of claim 5, wherein, The number of passive optical network device interfaces that need to be newly built in the machine room is obtained based on the relationship between the number of allocated users of the single existing passive optical network device interface of the machine room and the preset threshold value of the machine room, and includes: In the case where the number of allocated users of the single existing passive optical network device interface of the machine room is greater than the preset threshold value, the number of passive optical network device interfaces that need to be newly built in the machine room is obtained according to the quotient value between the second number of newly added users of the machine room and the preset threshold value of the machine room. In the case where the number of allocated users of the single existing passive optical network device interface of the machine room is less than the preset threshold value, it is determined that the machine room does not need to add passive optical network device interfaces.

7. The method of claim 5, wherein, The network construction scheme of the target area is generated according to the second number of newly added users of each machine room and the number of newly built passive optical network device interfaces of each machine room, and includes: The second number of newly added users of each machine room, the number of newly built passive optical network device interfaces of each machine room, and the number of idle passive optical network devices allocated to each machine room are input into a large language model, and the network construction scheme of the target area is generated according to the output of the large language model.

8. A network build plan generation apparatus, characterized by comprising: It includes: A prediction module configured to predict a first number of newly added users of each residential area according to regional data of a target area and network user data of each residence in the target area; A second number of newly added users determination module configured to determine a second number of newly added users of each machine room in the target area based on the first number of newly added users of each residence; A single interface allocated user number determination module configured to determine the number of allocated users of a single existing passive optical network device interface of each machine room based on the second number of newly added users of each machine room, the number of existing users of each machine room, and the first number of existing passive optical network device interfaces of each machine room; A newly built interface number determination module configured to, for each machine room, obtain the number of newly built passive optical network device interfaces of the machine room based on the relationship between the number of allocated users of the single existing passive optical network device interface of the machine room and the preset threshold value of the machine room. The network construction scheme generation module is configured to generate a network construction scheme of the target area according to the number of newly added users of each machine room and the number of newly built passive optical network equipment interfaces of each machine room.

9. A computer program product comprising a computer program, characterized in that, The computer program, when executed by a processor, implements the method of any one of claims 1 to 7.

10. An electronic device, comprising: Comprising: one or more processors; a memory device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1 to 7.

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