49 results about "It design" patented technology

This invention discloses an improved DBSCAN algorithm and a many-to-many matching algorithm for 6G vehicle-to-everything (V2X) networks, belonging to the field of V2X technology. It designs an improved density-based spatial application noise clustering algorithm to cluster more dispersed vehicles, employs a many-to-many matching algorithm to pair vehicles with auxiliary MEC servers, and designs a multi-agent-based task offloading mechanism to reduce latency and improve resource utilization efficiency. The improved DBSCAN algorithm proposed in this invention overcomes the sensitivity of parameter selection, does not require particularly precise parameter settings, performs well on datasets with uneven density, overcomes the influence of vehicle density on clustering results, and the proposed many-to-many matching mechanism improves the utilization of remaining vehicle computing resources and greatly alleviates the pressure on edge servers, while ensuring that high-priority tasks are computed first.

This invention discloses a distributed adaptive fault-tolerant control method and system for nonlinear inline systems, relating to the field of distributed control technology for nonlinear inline systems. The method includes: for each subsystem in the nonlinear inline system, constructing the actual output of each actuator in the subsystem based on the fault type of the actuator; the nonlinear inline system includes several subsystems; for each subsystem, constructing a local objective function, an error optimizer, an auxiliary system, high-gain parameters, and a control law, and generating an optimal error trajectory based on the local objective function and the error optimizer. At the upper level, this invention designs an error optimizer to generate the optimal error trajectory based on a local objective function that converges to zero; at the lower level, it designs a trajectory tracking fault-tolerant controller with the help of an auxiliary system, employing a dynamic high-gain approach to adaptively handle the effects of uncertain parameters, actuator faults, and unknown strong inline coupling.

In order to solve the problem that under the condition that a PMON program is not changed, the PMON program cannot provide inter-core memory isolation through two addresses of 0 * 8000000000000000 and 0 * 9000000000000000 configured by a direct mapping configuration window, the AMP architecture multi-core real-time operating system deployment method capable of meeting the inter-core memory isolation is designed on a Loongson platform. According to the multi-core deployment method for the AMP architecture operating system based on the Loongson platform disclosed by the invention, by designing a secondary bootstrap program, the mode that a PMON program directly loads an operating system mirror image is changed into the mode that the secondary bootstrap program is firstly loaded, and the operating system is started by the secondary bootstrap program. The secondary bootstrap program configures the MMU through a page table mapping address translation mode, so that operating systems between different cores can run in different address spaces, and an isolated running environment is provided. Once a certain operating system accesses the address space of other core operating systems, the system will report TLB refilling exceptions to prevent other core memories from being damaged, and therefore the inter-core memory isolation is achieved.

This invention relates to the field of new energy technology and discloses a short-term wind speed prediction method based on LSTM neural networks. The method first collects multi-dimensional historical wind speed data from wind farms and performs standardized preprocessing to construct a high-quality training set. Then, it designs and trains an LSTM neural network model that can effectively capture temporal dependencies. Finally, it obtains a high-precision prediction model through validation and optimization. In application, the preprocessed real-time data is input into the model to achieve quantitative prediction of wind speed for the next few hours. This method establishes an online performance evaluation and automatic update triggering mechanism based on the inherent volatility of the data, forming a complete prediction-evaluation-optimization closed loop. This allows the model to self-perceive performance degradation and autonomously trigger retraining, thereby overcoming the problem of performance degradation of traditional static models due to environmental changes after long-term deployment. Ultimately, this ensures the accuracy, adaptability, and industrial application value of the prediction model in long-term operation.

The present application relates to a kind of cabinet and line frame modeling method and device.The method part mainly includes: establishing the three-dimensional model and engineering drawing of general line frame parts, and determining relevant size parameters;Optimization design step: according to the structure and push-pull stroke of unit, determine the installation position of line frame, and according to the push-pull stroke and installation position parameters, the relevant size of line frame is optimized and designed;Automatic update step: the size parameter after optimization is transferred to three-dimensional model and engineering drawing to automatically update;Parameter saving step: the figure number, name, size parameter of line frame parts are saved in database.The present application can improve the design efficiency and product reusability of cabinet and line frame, and the size of line frame is optimized and designed, so that its design is more reasonable.

THE WAY IN WHICH THE ESSENTIAL ASPECT OF THE STRATEGE "FROM NOTHING - SOMETHING" IS IMPLEMENTED IN INFORMATION TECHNOLOGIES. The initial essence "Nothing" (0, Zero) of the method is the abstract essence. The mathematical model of the Projected Object Entity (PEO) is embodied in material, software, and mixed entity objects from various disciplines—the "something" of the method. The methodology of comparative cause-and-effect analysis is applied in the creation of the PEO, and the methodology of essential synthesis is used in its design: subject-specific and essential interdisciplinary properties of similarity, universal mathematical models in the form of orgraphs and their matrices, graphs with algorithms of nodes and their matrices, as well as essential identities, equations, and differential equations that reflect the balance of actions and counteractions.And since the professional and interdisciplinary properties of similarity for individual objects of different disciplines continue to apply, the transfer of the parental properties, qualities and the collective image of "nothing" and its "something" takes place "according to the image and likeness" of the essence.

The invention discloses a software engineering implementation method, and the method comprises the steps: business modeling: anchoring a demand source, and converting a business demand into a landing model; the software requirement specification specification is used for solidifying a requirement standard and forming a specification document based on the business modeling result; summary design: constructing a technical framework, joining demands and development, and macroscopically planning a system architecture; the framework is converted into an executable scheme, and coverage integration, implementation and development are achieved. According to the software engineering implementation process, a standardized'business modeling driving type 'specification is taken as a core, a five-level process model and a data model are used for constructing a business architecture core framework, full-link connection of'business demand-data logic-IT design-landing implementation' is broken through by means of a structured view, and complex processes / functions are deconstructed and split into micro-service interface-level granularity, micro-service interface-level granularity, micro-service interface-level granularity and micro-service interface-level granularity. Accurate correspondence and decoupling of the service component and the IT component are achieved, and finally efficient landing of the service architecture in the IT architecture is guaranteed.

This invention discloses a training method and apparatus for a BERT dispatch model based on multi-factor decision-making. The method includes: acquiring raw work order data and preprocessing it; filtering work orders with logical changes to obtain a training dataset; performing initial model training based on the training dataset to obtain an initial dispatch model; constructing a test dataset and performing multi-factor decision-making error analysis; data augmentation; secondary model training to generate an optimized model; iterative optimization and model deployment. This invention improves the dispatch model's ability to learn multi-factor correlation features and adapt to logical change scenarios by standardizing multi-dimensional decision factors, supplementing outdated standard data for cleaning, refining fusion training, conducting specialized error analysis, and expanding data with controllable quality. Simultaneously, it designs an optimized work order filtering mechanism for logical changes, ensuring the model quickly reaches the preset dispatch accuracy standard.

This invention proposes an automated construction organization design platform and its design method for water conservancy and hydropower projects. The platform includes a structured experience database system, a dynamic optimization calculation system for earthwork balance, an intelligent construction schedule generation system, an automated construction resource design system, and a 3D visualization and decision support system for the overall construction layout. The platform system uses the correlation data between building quantities and schedule time as a link to achieve data exchange and collaborative linkage. The design method includes: constructing and initializing the structured experience database system; automatically generating a construction schedule plan; outputting an earthwork balance scheme; automatically calculating and configuring labor force, work area, and facilities of each construction plant; generating a construction layout scheme and outputting it in 3D visualization. This invention realizes intelligent processing of the entire process of construction organization design calculation, resource supply planning, and site layout, significantly improving design efficiency and scheme accuracy, while also possessing good operability and system integration.

This invention aligns with the development trend of multi-scenario and multi-mode civilian radar. Addressing the core needs of multi-task adaptation, electromagnetic interference suppression, and flexible performance upgrades, it designs an intelligent radar signal processing architecture that meets the three standards of "functional scalability, performance upgradeability, modularity, and standardization," with deep decoupling of hardware and software and support for online software upgrades. This architecture adapts to the radar sensing and detection needs in complex electromagnetic environments. The architecture consists of three layers: hardware, system software, and intelligent applications. The hardware layer adopts a 3U VPX cableless platform, achieving flexible interconnection and expansion of multiple modules through star-flash technology. The system software layer extracts the common functionalities of radar imaging, altimetry, monopulse detection, and electronic reconnaissance, breaking them down into 4 categories and 8 standard modules, supporting dynamic module reconfiguration based on a linked list structure. The intelligent application layer includes 8 types of software applications (APPs). The intelligent decision-making APP generates radar operating modes, parameters, and timing strategies, driving other APPs to complete parameter configuration and achieving adaptive adaptation to multiple civilian scenarios.

This invention discloses a smart contract processing system and method based on the entire business process, belonging to the field of smart contract processing technology. It aims to solve technical problems in the existing service industry, such as opaque product rights transfer, low commission settlement efficiency, and profit-sharing disputes arising from refunds, changes, and modifications. The method uses a blockchain consortium blockchain as its underlying support, combining encryption algorithms and a smart contract engine. Through the status linkage of transaction vouchers, rights exchange vouchers, and commission vouchers, it achieves on-chain control of the entire business process from product booking, rights transfer, user change operations to commission settlement. Simultaneously, it designs a dynamic commission adjustment algorithm based on user behavior changes to ensure accurate and fair commission calculation. This invention achieves trusted collaboration of "core product + X + rights + commission," applicable to multiple service scenarios such as aviation, hotels, scenic spots, travel, retail, and lifestyle services, significantly improving user rights protection, channel commission settlement efficiency, and operational entity management efficiency.

This invention presents a threshold-free, privacy-preserving federated learning poisoning attack defense method, addressing the technical problems of intermediate information leakage, difficulty in distinguishing between benign and malicious updates, and difficulty in adapting to high-attack-ratio scenarios. The implementation includes: initialization; training and uploading parameters; secure K-means clustering on the server and threshold-free filtering based on benchmark gradients; server aggregation and dynamic benchmark updates; and updating the number of clusters. This invention uses a multi-party secure computation extension protocol to protect client gradient privacy in cluster-based federated learning poisoning attack defense. It designs a robust defense strategy of multi-cluster partitioning and combination filtering, performs secure K-means clustering, and securely compares different cluster combinations with server benchmark gradients. It does not require a preset malicious user ratio threshold and adaptively filters out benign update sets, achieving a balance between security, robustness, and scalability. It is applicable to federated learning systems involving a large number of heterogeneous entities, such as smart cities and connected vehicles.

This invention belongs to the field of cyberspace mapping, specifically involving a cluster-based method for network entity fingerprinting and network vulnerability situational awareness. First, it proposes a novel clustering-based network application fingerprinting method, constructing a database of known network node application type points. Through clustering algorithms, it efficiently classifies and labels collected network assets. Based on this, it automatically updates clustering features to discover new network entities and applications. Finally, it proposes a knowledge graph-based network vulnerability verification method, constructing a network entity information database, a vulnerability information database, and vulnerability verification knowledge atomic units. It designs and implements a vulnerability verification path generation algorithm to perform vulnerability verification on collected network assets, achieving automated vulnerability verification based on the knowledge graph. Ultimately, this results in a high-concurrency, multi-protocol, fast, and easily maintainable cyberspace asset detection system.

This invention discloses a data storage management method for aircraft testing, belonging to the technical field of aircraft testing and data storage management. The method includes database configuration management, database table creation management, database query management, and database monitoring management. Database configuration management includes login configuration and backup configuration; database table creation management includes data frame format initialization, modification, querying, display, exporting, table creation, and table deletion; database query management includes querying, processing, displaying, and exporting; database monitoring information includes the rate of row entry, total number of rows entered, and total space occupied. This invention designs a database table creation method and data storage rules, improving the efficiency of database table creation, reducing the number of tables created, and reducing the workload of maintenance personnel. Simultaneously, it designs data query and data monitoring methods, which are beneficial for multi-dimensional data analysis and use, and allow maintenance personnel to monitor data aggregation in real time.

A time modular system architecture capable of deforming energy industrial information productive inventories as a current demand topography evolves over time is provided. In embodiments, the system comprises an energy source, a productive component, a network component and a digital component. The energy source outputs energy. The productive component comprises a product (taken in the expansive meaning of any goods or services produced in the economy) output by the system. The network component connects the energy source to the productive component. The digital component determines shifts in demand of the productive component, manages automated systems, and optimizes the energy source based on the shifts in demand of the productive-consumptive component. Each of the energy source, network component and productive component are dynamically modified to optimize utilization based on supply and demand to deliver higher economic and societal intensity per unit of energy source(s).

This invention belongs to the field of data processing and discloses an edge accelerator and its design method for a distributed MoE large model architecture. The edge accelerator includes: a distributed vector systolic array module for acquiring initial text data and performing attention calculations to obtain initial text features; a nonlinear operation module for calculating expert scores on the initial text features to obtain the target expert score corresponding to each expert in the routing network; and a MoEGate module for performing expert selection and data rearrangement processing based on the target expert scores to obtain the mapping relationship between experts and tokens, and also for performing expert inference on the initial text features based on the mapping relationship between experts and tokens to output the text inference result. This invention, by adopting a distributed integrated architecture and integrating the MoEGate module, provides a sufficient bandwidth foundation and significantly improves inference throughput and energy efficiency, greatly accelerating the processing efficiency of text data.

This invention discloses a dynamic computing power allocation method for 5G smart chips supporting multimodal data, comprising the following steps: S1. Multimodal data acquisition and preprocessing; S2. Multimodal computing power demand prediction; S3. Initial allocation of computing power resources; S4. Dynamic computing power adjustment; S5. Energy consumption optimization and computing power constraints; S6. Computing power allocation feedback and model iteration; S7. Integrated computing and computing collaborative scheduling. This invention achieves deep collaboration between multimodal task priority, 5G communication rate, chip energy consumption, memory resources, and computing power allocation. It designs a dynamic weight allocation algorithm and cross-layer collaborative scheduling logic, considering not only the heterogeneity of multimodal data but also realizing the linkage between the 5G communication layer, data preprocessing layer, and chip computing layer.

The invention discloses a flexible job shop scheduling method based on a hybrid graph attention network and reward shaping, and belongs to the field of intelligent manufacturing and scheduling optimization. The method comprises the following steps: firstly, constructing a heterogeneous graph model, and integrating processes, machine nodes and multi-type adjacency relationships; a heterogeneous graph neural network (HGNN) is adopted to aggregate local features, a double Transform structure is combined to enhance a global context, and state representation fusing local and global information is generated; designing a scheduling strategy network based on an Actor-Critic framework, generating an optimal decision through Actor, and estimating a state value through Critic; a reward shaping mechanism is introduced, and a multi-dimensional reward function containing the maximum completion time improvement amount and the machine load balance degree is constructed; and a near-end strategy optimization algorithm is adopted to jointly train the network, so that adaptive scheduling optimization is realized. According to the method, the completion time can be effectively shortened, the machine load balance is improved, and the strategy learning stability and generalization ability are enhanced.

This invention discloses a federated graph synthesis method and system based on a differential privacy model, belonging to the field of federated learning technology. It is applied to a federated graph synthesis system comprising one server and multiple clients. The method includes a community detection stage, an information extraction stage, and a graph reconstruction stage. This method achieves global graph synthesis that satisfies edge differential privacy without centralized original sensitive edge data or cross-client interaction of original data, thus ensuring data privacy from an architectural perspective. It designs a noise-resistant edge statistics mechanism between supernodes, converting the weighted supernode graph into an unweighted undirected graph to reduce the impact of high noise on community detection in federated scenarios. It also designs a local community optimization mechanism to improve the accuracy of community structure detection. Furthermore, it proposes a fine-grained edge construction strategy, adaptively stopping client contribution value collection based on the connection strength of supernode pairs. Finally, it designs a heterogeneity-aware information extraction mechanism, allocating differentiated privacy budgets based on edge participation patterns.

The invention discloses a nuclear power plant DCS cabinet engineering design visual delivery method and device, and the method comprises the steps: building a knowledge warehouse based on the nuclear power plant DCS cabinet engineering design data; converting data in the knowledge warehouse into nodes with attributes by using an intelligent analysis engine; automatically generating a signal path network diagram according to the incidence relation of the data in the knowledge warehouse; and displaying the engineering design hardware equipment in a three-dimensional manner according to the signal path network diagram. According to the method, resources such as an upstream design input file and DCS design data are fully utilized, the DCS design file is converted into the data interconnection structure through digital and visual technologies, function design such as display and query is carried out based on the data interconnection structure, DCS design content is visually presented, function jump among information is taken into consideration, and the method and the device have the advantages of being high in practicability and easy to popularize. And the readability of the delivered data and the working efficiency of operation and maintenance are improved to a great extent.

The invention provides a public component development management method. The method comprises the following steps: establishing a code writing specification, a dynamic expansion mechanism, a code annotation specification and a version control strategy for developing a public component; establishing a development team training mechanism and a code review mechanism based on the code writing specification; designing dynamic parameters based on a dynamic expansion mechanism; optimizing the annotation document based on the code annotation specification; and managing the version of each public component in the public component library based on the version control strategy. By establishing a series of management specifications and optimization mechanisms, the development efficiency, quality and maintainability of the public component are improved, and the flexibility and expandability of the public component are enhanced. Through the implementation of the steps, it is ensured that developers can rapidly and easily integrate and call the public components, and meanwhile customized configuration and expansion can be conducted according to specific requirements of the project, so that the development efficiency is improved, the maintenance cost is reduced, and successful implementation of the project is promoted.

A quantum-key distributed (QKD)-enabled communication architecture it devises for networked microgrids (NMGs). A real-time QKD-enabled NMGs testbed built in an RTDS environment, and a novel two-level key pool sharing (TLKPS) strategy it designs to improve the system resilience against cyberattacks. In the QKD-based microgrid testbed design there is used a real-time power system simulator, i.e., RTDS, including the QKD modeling, hardware connection, communication network design, and QKD integration. By integrating QKD features into a real-time microgrid simulator, this testbed offers a flexible and programmable testing environment for evaluating the performance of QKD-enabled microgrids under a variety of scenarios.

This invention discloses a meta-reinforcement learning energy management method for the transient characteristics of hybrid electric vehicles. The method first pre-trains a deep reinforcement learning energy management strategy on a computationally efficient quasi-static longitudinal dynamics model to acquire basic control knowledge. Then, it constructs a high-precision target domain model that integrates lateral dynamics, system transient response, and delay characteristics. Next, it designs a meta-network architecture and a transfer loss function to quantify and extract source domain policy knowledge. Finally, in the target domain, a meta-reinforcement learning framework guides the lightweight target network to rapidly and adaptively optimize. This invention effectively solves the performance gap between simulation and reality and the challenges of vehicle deployment migration. It can obtain a high-performance control strategy adapted to real transient conditions within a limited number of iterations, significantly improving fuel economy and control robustness.

This invention relates to a distributed energy collaborative optimization method based on a cloud-edge-device architecture, belonging to the field of smart microgrid technology. Technical solution: S1. Define a four-layer cloud-edge-device architecture; S2. Information transmission stage: Information is reported upwards and circulated and transmitted at the same level; S3. Demand optimization stage: Demand is decomposed downwards and optimized collaboratively at the same level; S4. Energy flow stage: Energy is aggregated upwards and interacts and communicates at the same level. This invention, through its designed four-layer cloud-edge-device architecture, enables distributed energy to shift from centralized control to active participation in demand response. Based on this, a distributed energy collaborative optimization method based on the cloud-edge-device architecture is further designed, achieving full-domain collaborative optimization of distributed energy. Firstly, it reduces the response error of distributed energy; secondly, it effectively reduces the response time of distributed energy, solving the problem of excessive computing power in traditional centralized control; and thirdly, it reduces the operating cost of distributed energy, addressing the high operating cost of distributed energy.

This invention discloses a method for generating planar layout diagrams and 3D models for large-scale scenes, relating to the fields of 3D vision and layout diagram generation. The invention proposes a hierarchical scene layout generation method that explicitly decouples room topology and geometry to achieve planar layout generation for large scenes. It designs a "2D layout generation + 3D scene transformation" technical route to complete the generation of 3D models for large scenes; it proposes a size-aware semantic centroid heatmap representation, fusing room location and size information predicted by a graph transformer to ensure strong semantic alignment between the generated results and input constraints. It realizes the entire process of planar diagram vectorization and 3D transformation, achieving high-fidelity generation from 2D layout to 3D scene, and uses a large language model to realize the transformation of intelligent furniture layout and natural language description to scene diagram. This method can handle large scenes with more than ten rooms and is applicable to fields such as building information modeling, extended reality, and virtual emergency training.

1. Name of the product in this design: Graphical User Interface for Automatic Room Chart Conversion System for Electronic Devices. 2. Purpose of this design: To automatically generate DWG and PDF drawing files of real estate with different floor plans and units, and to perform related drawing file management and special layer settings. 3. The key design features of this product are the graphical user interface displayed on the screen of the electronic device. The key design features are the overall layout of the interface, the division of functional areas (such as the processing areas for layered subdivision diagrams and single-unit subdivision diagrams), the visual style and arrangement of each operation button (such as generate, delete, regenerate, etc.), the presentation of the file list, the display effect of the task progress bar, and the design of the area for modifying the name of special layers. 4. The image or photograph that best illustrates the design's key features: the front view. 5. This design is a graphical user interface, and its design focus is on the visual content displayed on the screen, omitting the rear view, left view, right view, top view, and bottom view. 6. Purpose of the graphical user interface: Main view: The initial main interface displayed by default after the system starts; the interface is divided into two file list areas on the left and right, which respectively display the file lists of the floor plan and the single-unit plan; the middle area has function operation buttons, including the function modules of "Number of Rooms in Guangzhou Achievement Households", "Delete All Single-Unit Plans", and "Regenerate Single-Unit Plans"; the lower left corner is the function selection option, and the lower right corner is the core operation button "Generate DWG and PDF", which is the trigger entry point for file generation operations. Figure 1 shows the main interface of the drawing generation tool, which includes processing options for layered and single-unit drawings. It displays a list of files to be processed or already generated, and provides main operation buttons such as "Description", "Delete All", "Regenerate", and "Generate DWG and PDF". This interface is triggered by clicking the "Generate DWG and PDF" button in the main view. The file list and functional area layout of the main view are retained, and the button in the lower right corner is changed to "Generating...". The progress bar at the bottom of the interface displays the task processing progress in real time, providing feedback to the user on the current file generation progress. Interface status change diagram 2: This diagram shows the status of the file generation task as completed or in progress. The progress bar (e.g., showing 100%) and status prompts (e.g., "Generation complete") provide feedback to the user on the current processing progress. This interface automatically jumps to the interface status change diagram 1 after the task is completed, with the progress bar showing 100% and the "Generation complete" and "Open folder after generation complete" buttons added. Users can click the "Open folder after generation complete" button to directly open the folder where the generated file is located and complete the entire process. 7. Human-computer interaction method of graphical user interface: Users can perform corresponding functions by clicking the operation buttons on the interface with a mouse or touch: Clicking the "Generate DWG and PDF" button in the main view triggers the file generation task, and the interface jumps to the interface state change diagram 1; after the task is completed, it automatically jumps to the interface state change diagram 2, and clicking the "Generation Completed Open Folder" button can access the generated files; the interface provides real-time feedback on the operation status and processing results to the user through file list, progress bar, pop-up window, and text prompts.

This invention discloses an online scalable configuration method and system for dynamically changing time-sensitive networks (TSNs), relating to the Internet of Things (IoT) field. The invention proposes an efficient inter-flow conflict detection mechanism based on multi-level flow grouping. By using a correlation analysis of flow period and offset, it avoids traditional conflict detection methods based on link maximal cliques and link hyperperiods, enabling rapid response to large-scale data flow conflict detection needs. It designs an online incremental method based on decoupling routing and scheduling, as well as offline pre-routing, accelerating the computation speed of routing and scheduling schemes while ensuring scheduling space. This invention reduces the computational complexity of data flow set hyperperiod sensitivity and the maximum link slot occupancy in TSNs, accelerating online scheduling and providing efficient conflict detection support for online scalable configuration.

This invention discloses a cloud network scenario-based diagnostic platform based on decision trees for end-to-end full-link network diagnosis. Addressing the root cause diagnosis problem when tenant end-to-end traffic anomalies occur, this invention proposes a multi-node full-link network diagnostic scheme based on decision trees. It designs decision logic based on expert experience, solving the decoupling and judgment of complex decision logic through root cause judgment with multiple combinations of conditions. It transforms the original independent condition judgments into state machine-based judgments, overcoming the challenges of long access links, numerous anomaly information, and difficulty in comprehensive root cause judgment faced by traditional diagnostic technologies. This diagnostic platform can be deployed on large-scale production cloud network operation and maintenance platforms and can be widely applied to the anomaly diagnosis of various network components such as virtual private networks, public network access, load balancing, and leased line access.

The invention discloses a Vue-based multi-dimensional user-defined query statistics method and system, and belongs to the field of data query statistics. Aiming at the technical pain points that in the prior art, the coupling degree of dimension configuration and a component is high, correlation verification lags behind, and component re-rendering is uncontrollable, JSON Schema definition is creatively expanded to define a metadata specification containing a'vueRender 'enhancement field, and dynamic decoupling and life cycle linkage of dimension configuration and Vue component rendering are achieved; designing a three-level association state depth-first traversal verification algorithm based on Vue response type dependency tracking, and realizing real-time accurate verification of query conditions through bidirectional linkage of a dimension association matrix and a dependency graph; proposing a life cycle aware dynamic weight LRU cache algorithm, and combining a component life cycle hook and a query frequency-data timeliness double-factor dynamic adjustment cache strategy; a fragment rendering mechanism in a large data volume scene is optimized, and collaborative optimization of intelligent cache management, dynamic cleaning and efficient component rendering is realized. Through full-link deep integration of metadata driving and Vue component life cycles, the problems of configuration efficiency, verification real-time performance and rendering performance in a multi-dimensional query scene are systematically solved. The method can be widely applied to data management systems, data analysis platforms and other scenes needing flexible query and statistics, and has remarkable technical advantages and practical value.

This invention belongs to the field of artificial intelligence communication technology and discloses a method and system for autonomous perception and dynamic collaborative scheduling of communication agents. Addressing the specific technical problems of coarse-grained network state perception, weak service adaptation decision-making capabilities, and lack of dynamic linkage in cross-domain collaborative scheduling of multiple agents, this invention constructs a global feature map of the communication network through the fusion and mining of multi-dimensional communication network perception data. It designs an autonomous decision-making modeling algorithm for communication agents that integrates service perception and proposes a multi-agent cross-domain dynamic collaborative scheduling mechanism based on distributed deep reinforcement learning. This achieves a technological upgrade for communication agents from passively executing instructions to actively perceiving the network, autonomously adapting to services, and performing cross-domain collaborative scheduling.