Communication network operation and maintenance analysis large model deep fusion system and method based on Vue

Abstract

The invention relates to the technical field of network operation and maintenance analysis, in particular to a communication network operation and maintenance analysis large model deep fusion system and method based on Vue, and the system comprises a front-end display layer, a Vue framework layer, a large model processing layer, and a data storage layer. The method has the beneficial effects that the large model is packaged into the Vue component and deeply fused with the front-end page, so that real-time display and interaction of the operation and maintenance analysis result are realized, and the working difficulty and time cost of operation and maintenance analysis personnel are reduced. And more accurate and reliable decision support is provided for operation and maintenance analysts by using the intelligent analysis and early warning capabilities of the large model, and the accuracy of operation and maintenance analysis is improved. By optimizing the rendering logic and the data processing flow of the front-end page and utilizing the parallel processing capability of the large model, the response speed and the performance of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of network operation and maintenance analysis, and specifically to a Vue-based communication network operation and maintenance analysis large model deep fusion system and method. Background Art

[0002] With the rapid development and increasing complexity of communications networks, operations and maintenance analysis faces increasing challenges. Traditional operations and maintenance analysis methods often rely on manual experience and simple data analysis tools, making them inadequate for large-scale, highly complex network operations and maintenance scenarios. While large models are increasingly being used in data processing and pattern recognition, their integrated application in communications network operations and maintenance analysis remains relatively limited.

[0003] Therefore, how to achieve the deep integration of communication network operation and maintenance analysis and front-end technology has become an important issue that needs to be urgently solved in the current field of communication network operation and maintenance. Summary of the Invention

[0004] The purpose of the present invention is to provide a Vue-based communication network operation and maintenance analysis large model deep fusion system and method to solve the problems raised in the above background technology.

[0005] To achieve the above objectives, the present invention provides the following technical solutions: a Vue-based communication network operation and maintenance analysis large model deep fusion system, comprising:

[0006] The front-end display layer is responsible for displaying the communication network operation and maintenance analysis results and interacting with users;

[0007] The Vue framework layer provides component-based development and responsive data binding functions, providing infrastructure support for the system's front-end development;

[0008] The large model processing layer is responsible for the key tasks of network data processing, pattern recognition, and anomaly detection, and performs intelligent analysis based on historical and real-time data of the communication network;

[0009] The data storage layer is used to store and manage various data required for communication network operation and maintenance analysis, and provide data support for all layers of the system.

[0010] Preferably, the large model processing layer and the front-end display layer are deeply integrated through the Vue framework layer. The specific integration method is:

[0011] The prediction and recognition functions of the large model are encapsulated as Vue components. Developers can introduce and use these large model components in the operation and maintenance analysis page just like using ordinary Vue components to achieve real-time display and interaction of operation and maintenance analysis results.

[0012] Preferably, real-time data synchronization is achieved between the front-end display layer and the large model processing layer through Vue's responsive data binding mechanism. Specifically, the operations of the operation and maintenance analysts on the front end will trigger the update and processing of the large model in real time, and the results processed by the large model processing layer will also be fed back to the front-end page in real time, thereby achieving dynamic adjustment and optimization of operation and maintenance analysis.

[0013] Preferably, the large model processing layer has intelligent analysis and early warning functions. Specifically, the large model processing layer performs intelligent analysis and generates early warning results based on the historical data and real-time data of the communication network. These analysis and early warning results can be directly displayed on the front-end page, providing intuitive and accurate decision support for operation and maintenance analysts.

[0014] Preferably, it also includes an efficient rendering and performance optimization mechanism, specifically: by optimizing the rendering logic and data processing flow of the front-end page, the loading speed and response performance of the front-end page are improved; at the same time, the parallel processing capabilities of the large model are utilized to achieve rapid processing and analysis of network data, so as to improve the operating efficiency of the entire system.

[0015] A method for a Vue-based communication network operation and maintenance analysis large model deep integration system, which is applied to a system including a front-end display layer, a Vue framework layer, a large model processing layer, and a data storage layer, and includes the following steps:

[0016] Build the system architecture and determine that the front-end display layer is responsible for the display and interaction of communication network operation and maintenance analysis results; the Vue framework layer provides component-based development and responsive data binding functions; the large model processing layer is responsible for network data processing, pattern recognition and anomaly detection tasks; the data storage layer is used to store and manage various data required for communication network operation and maintenance analysis.

[0017] Preferably, a component integration step is also included: the prediction and recognition functions of the large model are encapsulated as Vue components, so that developers can integrate the functions of the large model into the operation and maintenance analysis page by introducing and using these large model components during the development of the operation and maintenance analysis page, just like using ordinary Vue components, thereby realizing real-time display and interaction of the operation and maintenance analysis results.

[0018] Preferably, it also includes data binding and interaction steps: using Vue's responsive data binding mechanism, a real-time data synchronization channel is established between the front-end page and the large model processing layer; when the operation and maintenance analyst operates on the front-end page, the operation information will trigger the large model processing layer to update and process in real time; after the large model processing layer completes the processing, the processing results will be fed back to the front-end page in real time to achieve dynamic adjustment and optimization of operation and maintenance analysis.

[0019] Preferably, it also includes intelligent analysis and early warning steps: the large model processing layer obtains historical data and real-time data of the communication network from the data storage layer, performs intelligent analysis based on these data, determines whether there are abnormalities or potential risks in the network operation status, and generates early warning results; the analysis and early warning results are directly displayed on the front-end display layer to provide intuitive and accurate decision support for operation and maintenance analysts.

[0020] Preferably, it also includes efficient rendering and performance optimization steps: optimizing the rendering logic and data processing flow of the front-end page, reducing unnecessary rendering and data processing links, and improving the loading speed and response performance of the front-end page; at the same time, making full use of the parallel processing capabilities of the large model, performing parallel processing and analysis of network data to achieve rapid processing and analysis of network data and improve the operating efficiency of the entire system.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] The Vue-based communication network operation and maintenance analysis large model deep integration system and method proposed in this invention achieves real-time display and interaction of operation and maintenance analysis results by encapsulating the large model as a Vue component and deeply integrating it with the front-end page, reducing the work difficulty and time cost of operation and maintenance analysts. Utilizing the intelligent analysis and early warning capabilities of the large model, more accurate and reliable decision support is provided to operation and maintenance analysts, improving the accuracy of operation and maintenance analysis. By optimizing the rendering logic and data processing flow of the front-end page and leveraging the parallel processing capabilities of the large model, the system's response speed and performance are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0024] In order to clearly and completely describe the objectives and technical solutions of the present invention and make the advantages more clearly understood, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are part of the embodiments of the present invention, not all of them, and are only used to explain the embodiments of the present invention, not to limit the embodiments of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0025] In the first embodiment, the present invention provides a technical solution: a Vue-based communication network operation and maintenance analysis large-scale model deep integration system, comprising a front-end presentation layer, a Vue framework layer, a large-scale model processing layer, and a data storage layer. The front-end presentation layer is responsible for displaying and interacting with operation and maintenance analysis results; the Vue framework layer provides functions such as component-based development and responsive data binding; the large-scale model processing layer is responsible for tasks such as network data processing, pattern recognition, and anomaly detection; and the data storage layer is used to store and manage various data required for communication network operation and maintenance analysis.

[0026] Component integration: The prediction, recognition and other functions of the large model are encapsulated as Vue components. Developers can introduce and use these large model components in the operation and maintenance analysis page just like using ordinary Vue components, realizing real-time display and interaction of operation and maintenance analysis results.

[0027] Data Binding and Interaction: Leveraging Vue's responsive data binding mechanism, we achieve real-time data synchronization between the front-end page and the large model processing layer. Operations performed by operations analysts on the front-end trigger real-time updates and processing of the large model, and the processing results are fed back to the front-end page in real time, enabling dynamic adjustment and optimization of operations analysis.

[0028] Intelligent Analysis and Early Warning: The large-scale model processing layer performs intelligent analysis and early warning based on historical and real-time data from the communication network. These analysis and early warning results can be directly displayed on the front-end page, providing more intuitive and accurate decision support for operation and maintenance analysts.

[0029] Efficient rendering and performance optimization: By optimizing the rendering logic and data processing flow of the front-end page, the page loading speed and responsiveness are improved. At the same time, the parallel processing capabilities of large models are utilized to achieve rapid processing and analysis of network data.

[0030] Example 2. Based on Example 1, a method for a Vue-based communication network operation and maintenance analysis large model deep fusion system is proposed. The method is applied to a system including a front-end display layer, a Vue framework layer, a large model processing layer and a data storage layer, and includes the following steps: building a system architecture to determine that the front-end display layer is responsible for the display and interaction of the communication network operation and maintenance analysis results; the Vue framework layer provides component development and responsive data binding functions; the large model processing layer undertakes network data processing, pattern recognition and anomaly detection tasks; the data storage layer is used to store and manage various data required for communication network operation and maintenance analysis.

[0031] It also includes component integration steps: encapsulating the prediction and recognition functions of the large model into Vue components, so that developers can integrate the functions of the large model into the operation and maintenance analysis page by introducing and using these large model components during the development of the operation and maintenance analysis page, just like using ordinary Vue components, thereby realizing real-time display and interaction of operation and maintenance analysis results.

[0032] It also includes data binding and interaction steps: using Vue's responsive data binding mechanism to establish a real-time data synchronization channel between the front-end page and the large model processing layer; when the operation and maintenance analysts perform operations on the front-end page, the operation information will trigger the large model processing layer to update and process in real time; after the large model processing layer completes the processing, the processing results will be fed back to the front-end page in real time to achieve dynamic adjustment and optimization of operation and maintenance analysis.

[0033] It also includes intelligent analysis and early warning steps: the large model processing layer obtains historical data and real-time data of the communication network from the data storage layer, performs intelligent analysis based on these data, determines whether there are any abnormalities or potential risks in the network operation status, and generates early warning results; the analysis and early warning results are directly displayed on the front-end display layer to provide intuitive and accurate decision support for operation and maintenance analysts.

[0034] It also includes efficient rendering and performance optimization steps: optimizing the rendering logic and data processing flow of the front-end page, reducing unnecessary rendering and data processing links, and improving the loading speed and response performance of the front-end page; at the same time, making full use of the parallel processing capabilities of the large model to perform parallel processing and analysis of network data to achieve rapid processing and analysis of network data and improve the operating efficiency of the entire system.

[0035] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A Vue-based communication network operation and maintenance analysis large model deep integration system, characterized by: include: The front-end display layer is responsible for displaying the communication network operation and maintenance analysis results and interacting with users; The Vue framework layer provides component-based development and responsive data binding functions, providing infrastructure support for the system's front-end development; The large model processing layer is responsible for the key tasks of network data processing, pattern recognition, and anomaly detection, and performs intelligent analysis based on historical and real-time data of the communication network; The data storage layer is used to store and manage various data required for communication network operation and maintenance analysis, and provide data support for all layers of the system.

2. The Vue-based communication network operation and maintenance analysis large model deep fusion system according to claim 1 is characterized by: The large model processing layer and the front-end display layer are deeply integrated through the Vue framework layer. The specific integration method is as follows: The prediction and recognition functions of the large model are encapsulated as Vue components. Developers can introduce and use these large model components in the operation and maintenance analysis page just like using ordinary Vue components to achieve real-time display and interaction of operation and maintenance analysis results.

3. The Vue-based communication network operation and maintenance analysis large model deep fusion system according to claim 2 is characterized by: Real-time data synchronization is achieved between the front-end display layer and the large model processing layer through Vue's responsive data binding mechanism. Specifically, the operations of the operation and maintenance analysts on the front end will trigger the update and processing of the large model in real time, and the results processed by the large model processing layer will also be fed back to the front-end page in real time, thereby achieving dynamic adjustment and optimization of operation and maintenance analysis.

4. The Vue-based communication network operation and maintenance analysis large model deep fusion system according to claim 3 is characterized by: The large model processing layer has intelligent analysis and early warning functions. Specifically, the large model processing layer performs intelligent analysis and generates early warning results based on the historical data and real-time data of the communication network. These analysis and early warning results can be directly displayed on the front-end page, providing intuitive and accurate decision support for operation and maintenance analysts.

5. The Vue-based communication network operation and maintenance analysis large model deep fusion system according to claim 4 is characterized by: It also includes efficient rendering and performance optimization mechanisms, specifically: by optimizing the rendering logic and data processing flow of the front-end page, the loading speed and response performance of the front-end page are improved; at the same time, the parallel processing capabilities of the large model are utilized to achieve rapid processing and analysis of network data, thereby improving the operating efficiency of the entire system.

6. A method for a Vue-based communication network operation and maintenance analysis large model deep fusion system according to claim 5, characterized in that: The method is applied to a system including a front-end display layer, a Vue framework layer, a large model processing layer, and a data storage layer, and includes the following steps: Build the system architecture and determine that the front-end display layer is responsible for the display and interaction of communication network operation and maintenance analysis results; the Vue framework layer provides component-based development and responsive data binding functions; the large model processing layer is responsible for network data processing, pattern recognition and anomaly detection tasks; the data storage layer is used to store and manage various data required for communication network operation and maintenance analysis.

7. A method according to claim 6, characterized in that: It also includes component integration steps: encapsulating the prediction and recognition functions of the large model into Vue components, so that developers can integrate the functions of the large model into the operation and maintenance analysis page by introducing and using these large model components during the development of the operation and maintenance analysis page, just like using ordinary Vue components, thereby realizing real-time display and interaction of operation and maintenance analysis results.

8. A method according to claim 6, characterized in that: It also includes data binding and interaction steps: using Vue's responsive data binding mechanism to establish a real-time data synchronization channel between the front-end page and the large model processing layer; when the operation and maintenance analyst performs operations on the front-end page, the operation information will trigger the large model processing layer to update and process in real time; After the large model processing layer is completed, the processing results will be fed back to the front-end page in real time to achieve dynamic adjustment and optimization of operation and maintenance analysis.

9. A method according to claim 6, characterized in that: It also includes intelligent analysis and early warning steps: the large model processing layer obtains historical and real-time data of the communication network from the data storage layer, performs intelligent analysis based on this data, determines whether there are any abnormalities or potential risks in the network operation status, and generates early warning results; The analysis and warning results are directly displayed on the front-end display layer to provide intuitive and accurate decision support for operation and maintenance analysts.

10. A method according to claim 6, characterized in that: It also includes efficient rendering and performance optimization steps: optimizing the rendering logic and data processing flow of the front-end page, reducing unnecessary rendering and data processing links, and improving the loading speed and response performance of the front-end page; at the same time, making full use of the parallel processing capabilities of the large model to perform parallel processing and analysis of network data to achieve rapid processing and analysis of network data and improve the operating efficiency of the entire system.

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