Network asset management methods, devices, electronic equipment and storage media
By acquiring the anomaly identification characteristics of network assets and using anomaly identification models to automatically identify and manage network asset anomalies, the problem of low efficiency in existing technologies is solved, and efficient and automated network asset management is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- INSPUR TIANYUAN COMM INFORMATION SYST CO LTD
- Filing Date
- 2025-12-23
- Publication Date
- 2026-05-26
AI Technical Summary
The discovery of anomalies in network assets relies on manual inspections and queries, which is inefficient and poses a risk of long-term mismanagement and loss.
By acquiring anomaly identification characteristics of network assets, such as the frequency of network status changes, the distance of location changes, and the number of inventory turnovers, and inputting them into the network asset anomaly identification model for identification, anomaly identification results are generated, and key information is automatically pushed and maintenance work orders are generated, thereby realizing automated management of anomalies.
It improves the efficiency of identifying network asset anomalies, reduces manual intervention, ensures the integrity and accuracy of information, forms a refined management system across the entire chain, and avoids the loss of asset information.
Smart Images
Figure CN122089478A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of network asset management technology, and in particular to a network asset management method, apparatus, electronic device and storage medium. Background Technology
[0002] In the process of network asset operation and maintenance management, the number of network assets (such as base station radio frequency modules, optical transmission equipment, user terminals, etc.) is huge and widely distributed. The discovery of network asset anomalies relies on manual inspection and manual query, which is inefficient and there is a risk of long-term mismanagement and loss of network assets. Summary of the Invention
[0003] This invention provides a network asset management method, apparatus, electronic device, and storage medium to solve the technical problem of low efficiency in detecting network asset anomalies in the prior art.
[0004] This invention provides a network asset management method, comprising: Obtain anomaly identification features of network assets, including network status change frequency, location change distance, and inventory turnover frequency; The anomaly identification features are input into the network asset anomaly identification model to obtain the network asset anomaly identification result output by the network asset anomaly identification model. The network asset anomaly identification model is trained based on samples of the anomaly identification features and the corresponding labels of the samples.
[0005] According to a network asset management method provided by the present invention, before inputting the anomaly identification features into a network asset anomaly identification model and obtaining the network asset anomaly identification result output by the network asset anomaly identification model, the method further includes: The network asset anomaly detection model is iteratively trained using a training set that includes multiple anomaly detection feature samples and their labels.
[0006] According to a network asset management method provided by the present invention, after inputting the anomaly identification features into a network asset anomaly identification model and obtaining the network asset anomaly identification result output by the network asset anomaly identification model, the method further includes: If the network asset anomaly identification result is that the network asset is abnormal, then the key information of the network asset is extracted; the key information includes the serial number, location information, anomaly type and anomaly occurrence time; The key information is pushed to the target personnel's terminals.
[0007] According to a network asset management method provided by the present invention, if the network asset anomaly identification result is that the network asset is abnormal, after extracting the key information of the network asset, the method further includes: An operation and maintenance work order is generated based on the work order template corresponding to the aforementioned anomaly type. The maintenance work order is pushed to the maintenance personnel's terminal.
[0008] According to a network asset management method provided by the present invention, after pushing the maintenance work order to the maintenance personnel's terminal, the method further includes: After receiving the processing result of the maintenance work order uploaded by the maintenance personnel's terminal, the processing result is reviewed based on preset rules; If the processing result is approved, the maintenance work order will be closed. If the processing result fails the review, the processing result and the reason for the failure will be returned to the operation and maintenance personnel's terminal.
[0009] According to a network asset management method provided by the present invention, after returning the disposal result and the reason for the failure to pass the review to the maintenance personnel's terminal if the disposal result fails the review, the method further includes: If the number of times the processing result fails the review reaches a preset number, the operation and maintenance work order and the processing result will be pushed to the management personnel terminal.
[0010] According to a network asset management method provided by the present invention, the network asset management method further includes: After the network asset is taken offline, the serial number of the network asset, the offline action, and the offline time are recorded. Determine whether the network asset's serial number exists in each database and each maintenance work order. If the serial number of the network asset exists in the database, then the serial number of the network asset, the entry action, the entry time, the entry personnel information and the entry work order number are recorded, and the history status of the network asset is updated to be in the database or temporarily stored. If the network asset's serial number exists in the maintenance work order data, then the network asset's serial number, maintenance action, maintenance time, maintenance personnel information, and maintenance work order number are recorded, and the network asset's history status is updated to "in transit".
[0011] According to a network asset management method provided by the present invention, after determining whether the network asset's serial number exists in each database and each maintenance work order, the method further includes: If the serial number of the network asset is not found in any of the database data or the maintenance work order data, then the historical status of the network asset is updated to unknown.
[0012] The present invention also provides a network asset management device, comprising: The acquisition module is used to acquire anomaly identification features of network assets, including network status change frequency, location change distance, and inventory turnover frequency. The identification module is used to input the anomaly identification features into the network asset anomaly identification model to obtain the network asset anomaly identification result output by the network asset anomaly identification model. The network asset anomaly identification model is trained based on samples of the anomaly identification features and the corresponding labels of the samples.
[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the network asset management method as described above.
[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the network asset management method as described above.
[0015] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the network asset management method as described above.
[0016] The network asset management method, device, electronic device, and storage medium provided by this invention input the anomaly identification features of network assets into the network asset anomaly identification model to obtain the network asset anomaly identification results output by the network asset anomaly identification model. The discovery of network asset anomalies does not rely on manual inspection and manual query, thus improving the efficiency of network asset anomaly identification. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0018] Figure 1 This is a flowchart illustrating the network asset management method provided by the present invention.
[0019] Figure 2 This is a schematic diagram of the network asset management device provided by the present invention.
[0020] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation
[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.
[0022] The following is combined Figures 1-3 This invention describes the network asset management method, apparatus, electronic device, and storage medium provided by the present invention.
[0023] Figure 1 This is a flowchart illustrating the network asset management method provided by the present invention, as shown below. Figure 1 As shown, this includes, but is not limited to, steps S1 and S2.
[0024] Step S1: Obtain the anomaly identification features of network assets. The anomaly identification features include the frequency of network status changes, the distance of location changes, and the number of inventory turnovers.
[0025] Among these metrics, network status change frequency can be measured by the number of times a network asset goes offline within a day; if a network asset goes offline more than three times within a day, there is a high probability that the network asset is abnormal. Location change distance can be measured by the distance a network asset changes location within a day; if the distance changes location within a day exceeds 5 kilometers, there is a high probability that the network asset is abnormal. Inventory turnover can be measured by the number of times a network asset is received and issued within a day; if a network asset is received and issued more than three times within a day, there is a high probability that the network asset is abnormal.
[0026] The frequency of network status changes of network assets is obtained by analyzing the network status of network assets at different times. The distance of location changes of network assets is obtained by analyzing the location of network assets at different times. The number of inventory turnovers of network assets is obtained by analyzing the inventory status of network assets at different times.
[0027] The network status, location, and inventory status of network assets can be collected from data sources such as the Operation and Maintenance Center (OMC) data acquisition interface, the work order system, and the inventory system. Data can be collected periodically (e.g., every ≤10 seconds) or triggered by events (e.g., proactive push notifications when asset status changes). The OMC data acquisition interface is the technical channel or program interface used to automatically obtain real-time network asset status data from the OMC. The OMC data acquisition interface typically uses TCP / IP or SNMP (Simple Network Management Protocol) protocols. The work order system generally uses an API interface, while the inventory system typically uses Excel import or direct database connection.
[0028] Step S2: Input the anomaly identification features into the network asset anomaly identification model to obtain the network asset anomaly identification result output by the network asset anomaly identification model; the network asset anomaly identification model is trained based on the samples with anomaly identification features and the labels corresponding to the samples.
[0029] The network asset anomaly identification model has the function of identifying network asset anomalies based on anomaly identification features, and can identify anomalies such as high-frequency churn, abnormal location, and high-frequency inbound and outbound operations. The network asset anomaly identification model can be a hybrid model of random forest and long short-term memory (LSTM) network.
[0030] As can be seen from the above, the present invention inputs the anomaly identification features of network assets into the network asset anomaly identification model to obtain the network asset anomaly identification results output by the network asset anomaly identification model. The discovery of network asset anomalies does not rely on manual inspection and manual query, thus improving the efficiency of network asset anomaly identification.
[0031] In one embodiment, prior to step S2, the network asset management method of the present invention may further include: The network asset anomaly detection model is iteratively trained using a training set that includes multiple anomaly detection feature samples and their labels.
[0032] To enable the network asset anomaly detection model to accurately identify network asset anomalies, iterative training is required. When the network asset is normal, the label of the anomaly detection feature sample can be 0; when the network asset is abnormal, the label of the anomaly detection feature sample can be 1. The training set of this invention can be derived from anomaly detection features over the past three months. After iterative training of the network asset anomaly detection model, the anomaly detection accuracy can reach 95%. Common training methods can be used, which will not be described here.
[0033] By training the network asset anomaly identification model using a training set, the accuracy of the model in identifying anomalies can be improved.
[0034] In one embodiment, after step S2, the network asset management method of the present invention may further include: If the network asset anomaly identification result is that the network asset is abnormal, then extract the key information of the network asset; the key information includes the serial number, location information, anomaly type and anomaly occurrence time; Push key information to the target personnel's terminals.
[0035] The serial number serves as a unique identifier for the network asset, used to indicate an abnormal network asset; location information indicates the location of the abnormal network asset; the anomaly type can include network status anomaly, location anomaly, and inventory anomaly. The target personnel can be operations and maintenance personnel or management personnel.
[0036] Existing technologies notify relevant personnel via phone or email after an anomaly is detected in network assets, which is delayed and prone to incomplete information. This invention extracts key information about network assets upon anomaly detection and pushes this information to the target personnel's terminals, transforming manual notification into automated push notification. This significantly shortens the delay from anomaly detection to personnel awareness. The pushed information is comprehensive and complete, avoiding information omissions or errors that may occur during phone or email communication, thus improving communication efficiency.
[0037] In one embodiment, if the network asset anomaly identification result is that the network asset is abnormal, after extracting the key information of the network asset, the network asset management method of the present invention may further include: Generate maintenance work orders based on the work order templates corresponding to the exception types; Push maintenance work orders to the maintenance personnel's terminals.
[0038] Considering that different anomaly types require different handling methods, this invention can pre-design a work order template for each anomaly type, instructing maintenance personnel to handle each anomaly type. Due to the existence of work order templates, some content in maintenance work orders for the same anomaly type may be the same, but the serial numbers, locations, and anomaly occurrence times of network assets may differ.
[0039] In existing technologies, after receiving an anomaly alert, relevant personnel need to manually create and dispatch maintenance work orders, which is inefficient. This invention automatically generates standardized maintenance work orders based on work order templates and identified anomaly types, and directly pushes the generated work orders to the designated maintenance personnel's terminals, eliminating the need for manual work order creation and dispatch, and significantly improving the efficiency of anomaly handling. The work order templates ensure that the handling tasks and requirements for different anomaly types are standardized, improving the standardization of management.
[0040] In one embodiment, after pushing the maintenance work order to the maintenance personnel's terminal, the network asset management method of the present invention may further include: After receiving the handling result of the operation and maintenance work order uploaded by the operation and maintenance personnel's terminal, the handling result is reviewed based on preset rules; If the handling result is approved, the maintenance work order will be closed; If the processing result fails the review, the processing result and the reason for the failure will be returned to the operation and maintenance personnel's terminal.
[0041] The preset rules of this invention can be as follows: Rule 1: Approval passed (normal closed loop) If the handling result for the location anomaly is "Location verified, normal transfer, information updated", the number of characters in the handling description field is greater than 10, and the number of files in the attachment upload is greater than or equal to 2, then the review will be approved.
[0042] Rule 2: Review failed (incomplete information) If the processing result has been selected and the number of files uploaded as attachments is less than 2, the review will not be approved.
[0043] The reason for failure to pass the review may be: the handling result lacks on-site photo evidence. Please upload at least 2 photos as required.
[0044] In existing technologies, the handling results of maintenance work orders require manual review, the closed-loop process relies on manual follow-up, resulting in low efficiency and inconsistent standards. This invention, upon receiving the handling result, automatically reviews it according to preset rules. If the review is successful, the work order is automatically closed, completing the closed loop; if the review fails, it is automatically returned with a reason, requiring maintenance personnel to reprocess it. This achieves automated closed-loop processing of work order handling results. Automatic review through preset rules ensures consistent review standards for all handling results, avoiding the subjectivity and inconsistencies that may arise from manual review.
[0045] Furthermore, this invention forms a complete automated closed loop for handling anomalies, from "work order generation - dispatch - review - closure / return", which greatly improves the efficiency of anomaly handling and management.
[0046] In one embodiment, if the processing result fails the review, the processing result and the reason for the failure are returned to the maintenance personnel's terminal. The network asset management method of the present invention may further include: If the number of times the handling result fails the review reaches the preset number, the operation and maintenance work order and the handling result will be pushed to the management personnel terminal.
[0047] The preset number of attempts can be 2.
[0048] Considering that a maintenance work order might be repeatedly rejected and unable to close properly, leading to a deadlock or unresolved issues, this invention records the number of times a work order fails review. When this number reaches a preset threshold, the system no longer returns the work order to the original maintenance personnel but automatically pushes the work order and related processing records to the next higher-level administrator. This adds an exception handling path to the automated process, ensuring that difficult or poorly executed issues are promptly identified and reported, preventing problems from remaining unresolved. Administrators do not need to constantly monitor all work orders; the system automatically filters and pushes out work orders requiring administrator intervention, achieving precise and efficient management and supervision.
[0049] In one embodiment, the network asset management method of the present invention may further include: After a network asset is taken offline, record the network asset's serial number, offline action, and offline time. Determine whether there are network asset serial numbers in the data of each database and each maintenance work order; If the database contains the serial number of a network asset, record the serial number of the network asset, the entry action, the entry time, the entry personnel information, and the entry work order number, and update the network asset's history status to in stock or temporarily stored. If the maintenance work order data contains the serial number of a network asset, then record the serial number of the network asset, the maintenance action, the maintenance time, the maintenance personnel information, and the maintenance work order number, and update the network asset's history status to "in transit".
[0050] This invention records the network asset's history status as "online" after the network asset is added to the network. It obtains the network status of the network asset every day. If the current network status is "offline" and the network status was "online" yesterday, it inserts data such as the network asset's serial number, offline action, and offline time (current time) into the action table.
[0051] Then, it is determined whether there are serial numbers of off-network assets in the city warehouse data, spare parts warehouse data, network maintenance warehouse data, and outsourced maintenance work order data. The city warehouse is a regional or city-level central warehouse, the spare parts warehouse is a warehouse specifically used to store spare parts needed for maintenance, replacement, and repair, and the network maintenance warehouse is a temporary storage point for assets of the network maintenance department.
[0052] If the network asset's serial number exists in the database, it means the network asset has been deposited into the database. The network asset's history status is then updated to "In Stock" or "Temporarily Stored." Specifically, if the network asset's serial number exists in the city-level database or spare parts database, the history status is updated to "In Stock." If the network asset's serial number exists in the network maintenance database, the history status is updated to "Temporarily Stored." Then, the deposit times for each serial number in the deposit records are queried to determine if a serial number-deposit time pair exists in the action table. If no serial number-deposit time pair exists in the action table, the network asset's serial number, deposit action, deposit time, deposit personnel information, and deposit work order number are inserted into the action table.
[0053] If the maintenance work order data contains a network asset's serial number, it indicates that the network asset is under repair. The system then queries the maintenance work order data records for each maintenance time associated with that serial number to determine if a serial number-maintenance time pair exists in the action table. If no such pair exists, the system inserts the network asset's serial number, maintenance action, maintenance time, maintenance personnel information, and maintenance work order number into the action table, updating the network asset's history status to "in transit." If a serial number-maintenance time pair exists in the action table, the system updates the network asset's history status to "unknown."
[0054] Existing technologies cannot automatically and accurately determine whether network assets have entered the warehouse or are undergoing maintenance after they have gone offline, making it difficult to track their whereabouts. This invention uses the serial number of network assets to automatically query multiple independent databases, determines the whereabouts of network assets based on the query results, and records detailed information. It links data that were originally scattered across the OMC acquisition interface, inventory system, and work order system, forming a unified and coherent asset history table. This solves the problem of loss of contact after network assets go offline, and enables clear and automatic tracking of asset flow paths, providing a technical foundation for achieving refined end-to-end management that ensures assets are "not online, but in the warehouse."
[0055] In one embodiment, after determining whether there is a network asset serial number in each database and each maintenance work order, the network asset management method of the present invention may further include: If the serial number of the network asset is not found in any of the databases or maintenance work orders, then the historical status of the network asset will be updated to unknown.
[0056] When a network asset is neither in the inventory nor under maintenance, this invention updates its historical status to "unknown." By clearly identifying such assets, the system can automatically filter out high-risk assets that are truly likely to be lost, allowing managers to focus their efforts on tracking and auditing. This ensures that every off-network asset has a clear and recorded status, preventing historical gaps and thus avoiding the complete loss of assets at the information level.
[0057] The network asset management method of the present invention can use a relational database to store structured data such as serial numbers and time, and can sample a NoSQL database to store unstructured data such as maintenance descriptions and logs, ensuring efficient data reading and writing.
[0058] like Figure 2 As shown, the network asset management device provided by this invention includes, but is not limited to: The acquisition module is used to acquire anomaly identification features of network assets, including the frequency of network status changes, the distance of location changes, and the number of inventory turnovers. The identification module is used to input anomaly identification features into the network asset anomaly identification model to obtain the network asset anomaly identification results output by the network asset anomaly identification model; the network asset anomaly identification model is trained based on samples with anomaly identification features and the corresponding labels of the samples.
[0059] It should be noted that the network asset management device provided by the present invention can execute the network asset management method described in any of the above embodiments during specific operation, and this embodiment will not elaborate on this.
[0060] Figure 3 This is a schematic diagram of the electronic device provided by the present invention. The electronic device may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus. The processor can call logical instructions in the memory to execute a network asset management method. The method includes: acquiring anomaly identification features of network assets, including the frequency of network status changes, the distance of location changes, and the number of inventory turnovers; inputting the anomaly identification features into a network asset anomaly identification model to obtain the network asset anomaly identification result output by the network asset anomaly identification model.
[0061] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0062] On the other hand, the present invention also provides a computer program product, the computer program product including a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, and when the program instructions are executed by a computer, the computer is able to execute the network asset management method provided in the above embodiments, the method including: acquiring anomaly identification features of network assets, the anomaly identification features including network status change frequency, location change distance and inventory turnover times; inputting the anomaly identification features into a network asset anomaly identification model, and obtaining the network asset anomaly identification result output by the network asset anomaly identification model.
[0063] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the network asset management method provided in the above embodiments. The method includes: acquiring anomaly identification features of network assets, the anomaly identification features including network state change frequency, location change distance, and inventory turnover times; inputting the anomaly identification features into a network asset anomaly identification model to obtain the network asset anomaly identification result output by the network asset anomaly identification model.
[0064] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.
[0065] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.
[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for managing network assets, characterized in that, include: Obtain anomaly identification features of network assets, including network status change frequency, location change distance, and inventory turnover frequency; The anomaly identification features are input into the network asset anomaly identification model to obtain the network asset anomaly identification result output by the network asset anomaly identification model. The network asset anomaly identification model is trained based on samples of the anomaly identification features and the corresponding labels of the samples.
2. The network asset management method according to claim 1, characterized in that, Before inputting the anomaly identification features into the network asset anomaly identification model to obtain the network asset anomaly identification result output by the network asset anomaly identification model, the method further includes: The network asset anomaly detection model is iteratively trained using a training set that includes multiple anomaly detection feature samples and their labels.
3. The network asset management method according to claim 1, characterized in that, After inputting the anomaly identification features into the network asset anomaly identification model and obtaining the network asset anomaly identification result output by the network asset anomaly identification model, the method further includes: If the network asset anomaly identification result is that the network asset is abnormal, then the key information of the network asset is extracted; the key information includes the serial number, location information, anomaly type and anomaly occurrence time; The key information is pushed to the target personnel's terminals.
4. The network asset management method according to claim 3, characterized in that, If the network asset anomaly identification result is that the network asset is abnormal, then after extracting the key information of the network asset, the method further includes: An operation and maintenance work order is generated based on the work order template corresponding to the aforementioned anomaly type. The maintenance work order is pushed to the maintenance personnel's terminal.
5. The network asset management method according to claim 4, characterized in that, After pushing the maintenance work order to the maintenance personnel's terminal, the process also includes: After receiving the processing result of the maintenance work order uploaded by the maintenance personnel's terminal, the processing result is reviewed based on preset rules; If the processing result is approved, the maintenance work order will be closed. If the processing result fails the review, the processing result and the reason for the failure will be returned to the operation and maintenance personnel's terminal.
6. The network asset management method according to claim 5, characterized in that, If the processing result fails the review, the process of returning the processing result and the reason for the failure to the maintenance personnel's terminal also includes: If the number of times the processing result fails the review reaches a preset number, the operation and maintenance work order and the processing result will be pushed to the management personnel terminal.
7. The network asset management method according to claim 1, characterized in that, Also includes: After the network asset is taken offline, the serial number of the network asset, the offline action, and the offline time are recorded. Determine whether the network asset's serial number exists in each database and each maintenance work order. If the serial number of the network asset exists in the database, then the serial number of the network asset, the entry action, the entry time, the entry personnel information and the entry work order number are recorded, and the history status of the network asset is updated to be in the database or temporarily stored. If the network asset's serial number exists in the maintenance work order data, then the network asset's serial number, maintenance action, maintenance time, maintenance personnel information, and maintenance work order number are recorded, and the network asset's history status is updated to "in transit".
8. The network asset management method according to claim 7, characterized in that, After determining whether the network asset's serial number exists in each database and each maintenance work order, the process further includes: If the serial number of the network asset is not found in any of the database data or the maintenance work order data, then the historical status of the network asset is updated to unknown.
9. A network asset management device, characterized in that, include: The acquisition module is used to acquire anomaly identification features of network assets, including network status change frequency, location change distance, and inventory turnover frequency. The identification module is used to input the anomaly identification features into the network asset anomaly identification model to obtain the network asset anomaly identification result output by the network asset anomaly identification model. The network asset anomaly identification model is trained based on samples of the anomaly identification features and the corresponding labels of the samples.
10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the network asset management method as described in any one of claims 1 to 8.
11. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the network asset management method as described in any one of claims 1 to 8.
12. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the network asset management method as described in any one of claims 1 to 8.