Network operation and maintenance method and device, electronic equipment and storage medium

Abstract

The invention provides a network operation and maintenance method and device, electronic equipment and a storage medium, and relates to the field of artificial intelligence. The method comprises the following steps: receiving a voice instruction of a user, and determining a network operation and maintenance strategy based on the voice instruction; scheduling a plurality of digital employees to execute the operation and maintenance strategy based on the network operation and maintenance strategy; and after the operation and maintenance strategy is executed, feeding back a task processing result to the user. According to the network operation and maintenance method and device, the electronic equipment and the storage medium provided by the invention, the network operation and maintenance efficiency can be effectively improved, the network operation and maintenance cost is reduced, and the workload of operation and maintenance personnel is greatly reduced.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a network operation and maintenance method, device, electronic equipment and storage medium. Background Art

[0002] With the deepening of digital transformation and the rapid development of information technology, the scale of enterprise networks is expanding at an unprecedented rate, and business types are becoming increasingly diverse and complex.

[0003] Under this trend, the traditional network operation and maintenance methods have gradually exposed their limitations and shortcomings. Traditional operation and maintenance often rely on manual operation and experience judgment. Faced with massive network equipment, complex network topology and growing data traffic, operation and maintenance personnel need to spend a lot of time and energy to monitor, troubleshoot and maintain, resulting in low work efficiency and difficulty in responding to business needs and user feedback in a timely manner. In addition, as the scale of the network expands, more professional technicians are needed to maintain the normal operation of the network, which not only increases salary expenditures, but also comes with indirect costs such as training, management and personnel turnover. Frequent manual intervention may also lead to resource waste and efficiency loss. In addition, in a rapidly changing business environment, the emergence of network problems often requires the operation and maintenance team to quickly locate and solve the problem. However, due to its reliance on manual labor, the traditional operation and maintenance method has a long cycle from fault discovery to action, which is difficult to meet the needs of modern enterprises for high availability and rapid recovery of network services.

[0004] Therefore, how to improve network operation and maintenance efficiency and reduce network operation and maintenance costs has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The present invention provides a network operation and maintenance method, device, electronic device and storage medium, which are used to solve the defects of low network operation and maintenance efficiency and high network operation and maintenance cost in the prior art, so as to improve the network operation and maintenance efficiency and reduce the network operation and maintenance cost.

[0006] The present invention provides a network operation and maintenance method, comprising the following steps: receiving a user's voice command, and determining a network operation and maintenance strategy based on the voice command; Based on the network operation and maintenance strategy, dispatch multiple digital employees to execute the operation and maintenance strategy; After the operation and maintenance strategy is executed, the task processing result is fed back to the user.

[0007] According to a network operation and maintenance method provided by the present invention, the receiving of a user's voice instruction and determining a network operation and maintenance strategy based on the voice instruction include: Receive user's voice command; Recognizing the voice command to obtain a voice recognition result; The speech recognition result is analyzed using a machine learning model to obtain a network operation and maintenance strategy, which includes multiple target tasks and task execution processes.

[0008] According to a network operation and maintenance method provided by the present invention, the use of a machine learning model to analyze the speech recognition result to obtain a network operation and maintenance strategy includes: The machine learning model determines the network operation and maintenance intention of the user based on the speech recognition result; Splitting the network operation and maintenance intention into multiple target tasks; Determine the task execution process based on the network operation and maintenance intention and each target task.

[0009] According to a network operation and maintenance method provided by the present invention, after the operation and maintenance strategy is executed and the task processing result is fed back to the user, the method further includes: Based on the user's feedback, the parameters of the machine learning model are optimized.

[0010] According to a network operation and maintenance method provided by the present invention, before receiving a voice instruction from a user and determining a network operation and maintenance strategy based on the voice instruction, the method further includes: Acquire historical data of network operation and maintenance, wherein the historical data includes at least one of performance indicators and fault records; The machine learning model is trained based on the historical data.

[0011] According to a network operation and maintenance method provided by the present invention, each of the digital employees is used to perform different tasks.

[0012] The present invention also provides a network operation and maintenance device, comprising the following modules: A strategy determination module, used to: receive a user's voice command, and determine a network operation and maintenance strategy based on the voice command; A task scheduling module, used to: schedule multiple digital employees to execute the network operation and maintenance strategy based on the network operation and maintenance strategy; The result feedback module is used to: after the operation and maintenance strategy is executed, feed back the task processing result to the user.

[0013] According to a network operation and maintenance device provided by the present invention, the strategy determination module includes: The command receiving unit is used to: receive a user's voice command; A speech recognition unit, used to: recognize the speech instruction and obtain a speech recognition result; The speech analysis unit is used to: use a machine learning model to analyze the speech recognition result to obtain a network operation and maintenance strategy, wherein the network operation and maintenance strategy includes multiple target tasks and task execution processes.

[0014] According to a network operation and maintenance device provided by the present invention, the speech analysis unit is specifically used for: The machine learning model determines the network operation and maintenance intention of the user based on the speech recognition result; Splitting the network operation and maintenance intention into multiple target tasks; Determine the task execution process based on the network operation and maintenance intention and each target task.

[0015] According to a network operation and maintenance device provided by the present invention, the network operation and maintenance device also includes: A model optimization module is used to optimize the parameters of the machine learning model based on the feedback from the users.

[0016] According to a network operation and maintenance device provided by the present invention, the network operation and maintenance device also includes: A model training module is used to: obtain historical data of network operation and maintenance, wherein the historical data includes at least one of performance indicators and fault records; The machine learning model is trained based on the historical data.

[0017] According to a network operation and maintenance device provided by the present invention, each of the digital employees is used to perform different tasks.

[0018] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any of the network operation and maintenance methods described above is implemented.

[0019] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the network operation and maintenance method described in any one of the above is implemented.

[0020] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the network operation and maintenance method described above is implemented.

[0021] The network operation and maintenance method, device, electronic device and storage medium provided by the present invention receive the user's voice command, and determine the network operation and maintenance strategy based on the voice command, that is, through human-computer interaction, determine the user's needs, and automatically determine the network operation and maintenance strategy according to the user's needs, which provides a basis for subsequent network operation and maintenance; based on the network operation and maintenance strategy, dispatch multiple digital employees to execute the operation and maintenance strategy, that is, automatically execute repetitive operation and maintenance tasks, without the need for operation and maintenance personnel to perform repetitive work, improve operation and maintenance efficiency and reduce labor costs; after the operation and maintenance strategy is executed, the task processing results are fed back to the user. In summary, the network operation and maintenance method provided by the present invention can effectively improve network operation and maintenance efficiency and reduce network operation and maintenance costs, greatly reducing the workload of operation and maintenance personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 This is one of the flow charts of the network operation and maintenance method provided by the present invention.

[0024] Figure 2 This is the second flow chart of the network operation and maintenance method provided by the present invention.

[0025] Figure 3 It is a structural schematic diagram of the network operation and maintenance device provided by the present invention.

[0026] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] It should be noted that in the description of the embodiments of the present invention, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "include one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements. The orientation or position relationship indicated by the terms "upper", "lower" and the like is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be a connection between two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0029] The terms "first", "second", etc. in this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0030] With the deepening of digital transformation and the rapid development of information technology, the scale of enterprise networks is expanding at an unprecedented rate, and business types are becoming increasingly diverse and complex.

[0031] Under this trend, the traditional network operation and maintenance methods have gradually exposed their limitations and shortcomings. Traditional operation and maintenance often rely on manual operation and experience judgment. Faced with massive network equipment, complex network topology and growing data traffic, operation and maintenance personnel need to spend a lot of time and energy to monitor, troubleshoot and maintain, resulting in low work efficiency and difficulty in responding to business needs and user feedback in a timely manner. In addition, as the scale of the network expands, more professional technicians are needed to maintain the normal operation of the network, which not only increases salary expenditures, but also comes with indirect costs such as training, management and personnel turnover. Frequent manual intervention may also lead to resource waste and efficiency loss. In addition, in a rapidly changing business environment, the emergence of network problems often requires the operation and maintenance team to quickly locate and solve the problem. However, due to its reliance on manual labor, the traditional operation and maintenance method has a long cycle from fault discovery to action, which is difficult to meet the needs of modern enterprises for high availability and rapid recovery of network services.

[0032] Therefore, how to improve network operation and maintenance efficiency and reduce network operation and maintenance costs has become a technical problem that needs to be solved urgently.

[0033] In view of the above problems, the present invention provides a network operation and maintenance method, device, electronic device and storage medium. Figure 1-Figure 4 The present invention describes a network operation and maintenance method, device, electronic device and storage medium.

[0034] Figure 1 It is one of the flow charts of the network operation and maintenance method provided by the present invention; Figure 2 This is the second flow chart of the network operation and maintenance method provided by the present invention; like Figure 1 and Figure 2 As shown, the network operation and maintenance method may include the following steps: S110, receiving a voice command from a user, and determining a network operation and maintenance strategy based on the voice command; S120, based on the network operation and maintenance strategy, dispatching multiple digital employees to execute the operation and maintenance strategy; S130, after the operation and maintenance strategy is executed, the task processing result is fed back to the user.

[0035] It should be noted that the execution subject of the network operation and maintenance method provided in the embodiments of the present application can be a server, a computer device, such as an ultra-mobile personal computer (UMPC), a netbook, etc., or a network operation and maintenance system, the front end of which is located in the computer device to achieve human-computer interaction with the user, and the back end is located in the server to achieve data storage and calculation. For ease of understanding, the following embodiments take the network operation and maintenance system as the execution subject, and illustrate the network operation and maintenance method provided by the present invention.

[0036] In S110, the user can use natural language to interact with the network operation and maintenance system through the foreground window. Specifically, the user can ask questions or require the network operation and maintenance system to perform corresponding tasks, such as the user's request to "query the current TOP10 alarm base stations." After receiving the user's voice command, the natural language understanding (NLU) technology is used to understand the user's natural language command, thereby determining the network operation and maintenance strategy.

[0037] Optionally, AI Agent technology is used to implement human-computer interaction, providing a user-friendly interface to enable interaction between operation and maintenance personnel and AI Agent.

[0038] In S120, digital employees, or digital robots, are used to perform rule-based, repetitive tasks that were originally completed by humans. They automatically process data without the need for human intervention and realize the automatic execution of operation and maintenance strategies.

[0039] In S130, after executing the operation and maintenance strategy, the system will feed back the processing results to the user in the form of natural language. Specifically, the task processing results can be fed back to the user through methods including but not limited to a visual interface, voice, text message, email, etc.

[0040] The network operation and maintenance method provided in the embodiment of the present invention receives the user's voice command, and determines the network operation and maintenance strategy based on the voice command, that is, through human-computer interaction, determines the user's needs, and automatically determines the network operation and maintenance strategy according to the user's needs, which provides a basis for subsequent network operation and maintenance; based on the network operation and maintenance strategy, dispatches multiple digital employees to execute the operation and maintenance strategy, that is, automatically executes repetitive operation and maintenance tasks, without the need for operation and maintenance personnel to perform repetitive work, improves operation and maintenance efficiency, and reduces labor costs; after the operation and maintenance strategy is executed, the task processing results are fed back to the user. In summary, the network operation and maintenance method provided by the present invention can effectively improve network operation and maintenance efficiency and reduce network operation and maintenance costs, greatly reducing the workload of operation and maintenance personnel.

[0041] In an optional embodiment, the receiving a voice instruction from a user and determining a network operation and maintenance strategy based on the voice instruction includes: Receive user's voice command; Recognizing the voice command to obtain a voice recognition result; The speech recognition result is analyzed using a machine learning model to obtain a network operation and maintenance strategy, which includes multiple target tasks and task execution processes.

[0042] It should be noted that the method used for speech recognition is not limited here; the machine learning model is not limited here. For example, the machine learning model uses a large language model (LLM).

[0043] Here, the task execution process refers to the execution order of each target task among the multiple target tasks.

[0044] The network operation and maintenance method provided in the embodiment of the present invention recognizes the user's voice command, parses it to obtain a network operation and maintenance strategy including multiple target tasks and task execution processes, and realizes autonomous determination of specific operation and maintenance tasks based on the user's voice command, thereby providing intelligent analysis and decision support for network operation and maintenance, and providing a basis for the scheduling and execution of subsequent tasks.

[0045] Further optionally, the using of a machine learning model to analyze the speech recognition result to obtain a network operation and maintenance strategy includes: The machine learning model determines the network operation and maintenance intention of the user based on the speech recognition result; Splitting the network operation and maintenance intention into multiple target tasks; Determine the task execution process based on the network operation and maintenance intention and each target task.

[0046] Here, the user's voice commands are recognized through natural language processing methods, the user's natural language commands are understood, the user's query intentions are identified, and the user's intentions are split into several tasks according to the user's input. The AI ​​Agent technology is used to orchestrate the intention execution process according to the intention recognition and splitting results, and the process tasks are dispatched to the corresponding RPA (Robotic process automation) "digital employees". AI Agent is an artificial intelligence agent that uses various artificial intelligence technologies, such as machine learning, natural language processing, computer vision, and decision theory, to perceive the environment, understand the situation, and respond or take actions, solving complex problems and performing tasks without direct human intervention.

[0047] The network operation and maintenance method provided by the embodiment of the present invention is that the AI ​​Agent autonomously arranges the intention execution process according to the user's intention, realizes the automation of network operation and maintenance, reduces manpower requirements, and achieves effective cost control.

[0048] Optionally, multiple AI Agents can collaborate to orchestrate and schedule the task execution process.

[0049] Specifically, one of the multiple AI Agents (hereinafter referred to as the super duty agent) can be responsible for determining the network operation and maintenance strategy according to the user's intention, that is, determining multiple target tasks according to the user's intention and arranging the task execution process, and each of the other AI Agents is responsible for scheduling specific digital employees, for example, one AI Agent is responsible for scheduling "alarm query digital employees", and one AI Agent is responsible for scheduling "abnormal warning digital employees" and "fault location digital employees". It can be understood that the number of digital employees that each AI Agent is responsible for scheduling is unlimited and can be the same or different; each AI Agent is responsible for scheduling different digital employees, that is, one digital employee can only be scheduled by one AI Agent, simplifying the digital employee scheduling plan.

[0050] In one embodiment, each AI Agent can dispatch any digital employee; in the specific implementation process, each AI Agent determines the digital employee it needs to dispatch in the current network operation and maintenance task according to the instructions of the super duty manager Agent.

[0051] In another embodiment, each AI Agent can schedule several designated digital employees, and one digital employee can be scheduled by multiple AI Agents. In the specific implementation process, the super duty manager Agent specifies the digital employees that each AI Agent needs to schedule in the current network operation and maintenance task according to the current operation status of each AI Agent, thereby realizing task scheduling according to the actual operation status of the AI ​​Agent and improving the task scheduling efficiency. Moreover, one digital employee can be scheduled by multiple AI Agents. When one AI Agent fails or is busy, other AI Agents can perform task scheduling to improve the fault tolerance of task scheduling.

[0052] In an optional embodiment, after the operation and maintenance strategy is executed, after the task processing result is fed back to the user, the method further includes: Based on the user's feedback, the parameters of the machine learning model are optimized.

[0053] The network operation and maintenance method provided by the embodiment of the present invention continuously learns and optimizes the model according to user feedback and new data, thereby improving the accuracy of operation and maintenance strategy generation and enhancing user experience.

[0054] In an optional embodiment, before receiving a voice instruction from a user and determining a network operation and maintenance strategy based on the voice instruction, the method further includes: Acquire historical data of network operation and maintenance, wherein the historical data includes at least one of performance indicators and fault records; The machine learning model is trained based on the historical data.

[0055] Specifically, various types of data on historical network operation and maintenance are obtained, which may include but are not limited to network performance indicators and network fault records. Fault records may include but are not limited to performance indicators at the time of network failure, causes of network failures, solutions to the failures, and network performance indicators after the failures are solved; model training is performed based on these historical data to provide data support for the model, support task scheduling and conclusions.

[0056] The network operation and maintenance method provided in the embodiment of the present invention trains a machine learning model that provides a network operation and maintenance strategy based on historical data of network operation and maintenance, optimizes the network operation and maintenance strategy based on historical big data, and the trained model can effectively make network operation and maintenance strategy decisions.

[0057] Based on any of the above embodiments, each of the digital employees is used to perform different tasks.

[0058] like Figure 2 As shown, digital employees may include but are not limited to alarm query digital employees, supervision notification digital employees, abnormal warning digital employees, and fault location digital employees. Each digital employee has different capabilities, that is, each digital employee is used to perform specific tasks. After obtaining the network operation and maintenance strategy, the corresponding digital employee is determined based on the target task in the network operation and maintenance strategy, and the corresponding digital employee is scheduled in sequence according to the task execution process to perform the corresponding target task.

[0059] Here, RPA technology can be used to achieve task scheduling and automated execution. Specifically, according to the instructions of AIAgent, the corresponding automated tasks are scheduled and executed; through RPA technology, repetitive operation and maintenance tasks such as configuration changes and data backup can be automatically executed.

[0060] The network operation and maintenance device provided by the present invention is described below. The network operation and maintenance device described below and the network operation and maintenance method described above can be referenced to each other.

[0061] Figure 3 is a schematic diagram of the structure of the network operation and maintenance device provided by the present invention, such as Figure 3As shown, the network operation and maintenance device may include: The strategy determination module 310 is used to: receive a user's voice instruction, and determine a network operation and maintenance strategy based on the voice instruction; The task scheduling module 320 is used to: schedule multiple digital employees to execute the operation and maintenance strategy based on the network operation and maintenance strategy; The result feedback module 330 is used to feed back the task processing result to the user after the operation and maintenance strategy is executed.

[0062] The network operation and maintenance device provided in the embodiment of the present invention receives the user's voice command, and determines the network operation and maintenance strategy based on the voice command, that is, through human-computer interaction, determines the user's needs, and automatically determines the network operation and maintenance strategy according to the user's needs, which provides a basis for subsequent network operation and maintenance; based on the network operation and maintenance strategy, dispatches multiple digital employees to execute the operation and maintenance strategy, that is, automatically executes repetitive operation and maintenance tasks, without the need for operation and maintenance personnel to perform repetitive work, improves operation and maintenance efficiency, and reduces labor costs; after the operation and maintenance strategy is executed, the task processing results are fed back to the user. In summary, the network operation and maintenance method provided by the present invention can effectively improve the network operation and maintenance efficiency and reduce the network operation and maintenance cost, greatly reducing the workload of operation and maintenance personnel.

[0063] In an optional embodiment, the policy determination module 310 includes: The command receiving unit is used to: receive a user's voice command; A speech recognition unit, used to: recognize the speech instruction and obtain a speech recognition result; The speech analysis unit is used to: use a machine learning model to analyze the speech recognition result to obtain a network operation and maintenance strategy, wherein the network operation and maintenance strategy includes multiple target tasks and task execution processes.

[0064] In an optional embodiment, the speech analysis unit is specifically used for: The machine learning model determines the network operation and maintenance intention of the user based on the speech recognition result; Splitting the network operation and maintenance intention into multiple target tasks; Determine the task execution process based on the network operation and maintenance intention and each target task.

[0065] In an optional embodiment, the network operation and maintenance device further includes: A model optimization module is used to optimize the parameters of the machine learning model based on the feedback from the users.

[0066] In an optional embodiment, the network operation and maintenance device further includes: A model training module is used to: obtain historical data of network operation and maintenance, wherein the historical data includes at least one of performance indicators and fault records; The machine learning model is trained based on the historical data.

[0067] In an optional embodiment, each of the digital employees is used to perform different tasks.

[0068] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communications interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the network operation and maintenance method, which includes: receiving a user's voice instruction, determining a network operation and maintenance strategy based on the voice instruction; scheduling multiple digital employees to execute the operation and maintenance strategy based on the network operation and maintenance strategy; and after the operation and maintenance strategy is executed, feeding back the task processing result to the user.

[0069] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0070] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the network operation and maintenance method provided by the above methods. The method includes: receiving a user's voice command, and determining a network operation and maintenance strategy based on the voice command; based on the network operation and maintenance strategy, scheduling multiple digital employees to execute the operation and maintenance strategy; after the operation and maintenance strategy is executed, feeding back the task processing results to the user.

[0071] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it is implemented to execute the network operation and maintenance method provided by the above-mentioned methods. The method includes: receiving a user's voice command, and determining a network operation and maintenance strategy based on the voice command; based on the network operation and maintenance strategy, scheduling multiple digital employees to execute the operation and maintenance strategy; after the operation and maintenance strategy is executed, feeding back the task processing result to the user.

[0072] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0073] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A network operation and maintenance method, characterized in that: include: receiving a user's voice command, and determining a network operation and maintenance strategy based on the voice command; Based on the network operation and maintenance strategy, dispatch multiple digital employees to execute the operation and maintenance strategy; After the operation and maintenance strategy is executed, the task processing result is fed back to the user.

2. The network operation and maintenance method according to claim 1, characterized in that: The receiving a voice command from a user and determining a network operation and maintenance strategy based on the voice command includes: Receive user's voice command; Recognizing the voice command to obtain a voice recognition result; The speech recognition result is analyzed using a machine learning model to obtain a network operation and maintenance strategy, which includes multiple target tasks and task execution processes.

3. The network operation and maintenance method according to claim 2, characterized in that: The method of using a machine learning model to analyze the speech recognition result and obtain a network operation and maintenance strategy includes: The machine learning model determines the network operation and maintenance intention of the user based on the speech recognition result; Splitting the network operation and maintenance intention into multiple target tasks; Determine the task execution process based on the network operation and maintenance intention and each target task.

4. The network operation and maintenance method according to claim 2, characterized in that: After the operation and maintenance strategy is executed, after the task processing result is fed back to the user, the method further includes: Based on the user's feedback, the parameters of the machine learning model are optimized.

5. The network operation and maintenance method according to claim 2, characterized in that: Before receiving the user's voice command and determining the network operation and maintenance strategy based on the voice command, the method further includes: Acquire historical data of network operation and maintenance, wherein the historical data includes at least one of performance indicators and fault records; The machine learning model is trained based on the historical data.

6. The network operation and maintenance method according to any one of claims 1 to 5, characterized in that: Each of the digital employees is used to perform different tasks.

7. A network operation and maintenance device, characterized in that: include: A strategy determination module, configured to: receive a user's voice command, and determine a network operation and maintenance strategy based on the voice command; A task scheduling module, used to: schedule multiple digital employees to execute the network operation and maintenance strategy based on the network operation and maintenance strategy; The result feedback module is used to: after the operation and maintenance strategy is executed, feed back the task processing result to the user.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the network operation and maintenance method as described in any one of claims 1 to 6 is implemented.

9. 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, the network operation and maintenance method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the network operation and maintenance method according to any one of claims 1 to 6 is implemented.

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