16418results about How to "Reduce workload" patented technology

The invention provides a new material production process parameter optimization method and system based on artificial intelligence, and relates to the technical field of parameter optimization, and the method comprises the steps: constructing a multi-dimensional process parameter feature space, collecting and preprocessing process parameters, extracting correlation features through a deep convolutional neural network, and building a parameter feature space model; generating a technological parameter collaborative optimization model, constructing a multi-objective optimization function, and performing iterative optimization by using reinforcement learning and an improved ant colony algorithm; and performing process parameter adaptive control, constructing a dynamic control interval, collecting parameters in real time and performing adaptive adjustment to realize closed-loop control and model dynamic update.

The invention discloses a medical visual question-answering method and system based on multi-task modeling, and the method comprises the steps: carrying out the feature extraction of a to-be-analyzed medical image through a visual encoder, obtaining an image feature, inputting a preliminary question instruction and historical question-answering data into a dialogue large model to generate a question instruction, and obtaining a text feature through a text encoder; carrying out feature fusion on the obtained text features and image features, and carrying out self-attention image importance weighting processing and image-text alignment to obtain image-text fusion representation; and inputting a multi-target output projection layer, carrying out multi-task prediction, outputting question answers, image categories and important region masks, inputting the question answers and the image categories into a dialogue large model, and finally generating diagnosis opinions with detailed description in combination with dialogue context and multi-round interaction data and in combination with the important region masks. According to the invention, the interaction experience and the performance of the question and answer system are improved, and more accurate medical diagnosis in multi-modal complex information is facilitated.

The invention belongs to the technical field of data security, and discloses a data management method based on a data resource security identification level, and the method achieves the automatic and intelligent decision making: achieves the data classification and the automatic identification of the security level through a machine learning and deep learning model, remarkably reduces the manual intervention, and improves the efficiency and accuracy. And dynamic real-time performance: in combination with a risk assessment model, the system can detect abnormal behaviors in real time and dynamically adjust a security policy in a data flow process, so as to ensure that the sensitive data is properly protected in different scenes. And security and compliance: a log auditing module ensures the traceability of all data operations, improves the response capability to potential risks through an anomaly detection algorithm, and provides effective compliance guarantee for data security governance. And the system can be compatible with various data sources, supports configuration and execution of various security policies, and is suitable for data security management requirements of different industries (such as finance and medical treatment).

The invention discloses an electric power inspection system and method based on an unmanned aerial vehicle, which are used for solving the problem of how to realize autonomous path planning of the unmanned aerial vehicle in a complex three-dimensional environment so as to reduce redundant flight time and improve inspection efficiency. The electric power inspection system comprises a path planning unit, an obstacle avoidance positioning unit and a dynamic obstacle avoidance unit which are connected in sequence. Three-dimensional map data and real-time environment information of a to-be-inspected power line are obtained through a path planning unit, real-time path planning is carried out based on the three-dimensional map data and the real-time environment information, and an optimal flight path of the unmanned aerial vehicle is dynamically generated; obstacle avoidance positioning is carried out on the power equipment on the optimal flight path and the surrounding environment thereof through an obstacle avoidance positioning unit, and real-time positioning information of an obstacle is generated; and a dynamic obstacle avoidance unit constructs a dynamic obstacle map based on the real-time positioning information, and automatically plans an obstacle avoidance strategy according to the dynamic obstacle map, so that the unmanned aerial vehicle realizes dynamic obstacle avoidance based on the obstacle avoidance strategy.

The invention discloses a link reliability tracking and optimizing method combined with real-time monitoring, and relates to the technical field of data transmission. Comprising the following steps: constructing a topological graph of a full link based on component information and a data flow relationship of a data medium station, and deploying a data acquisition probe to acquire link data in real time; a potential fault or an abnormal link is automatically identified; based on the data map, sorting the data dependency relationship of the upstream and downstream of the link, recording the relevance and dependency path of each component, and forming an accurate link blood relationship map; link abnormal conditions are captured and backtracked, log information is summarized in a unified mode, and centralized analysis and problem positioning are carried out; and on the basis of operation historical data of the link, according to the time sequence prediction model, identifying a bottleneck and a high-risk area in the link, dynamically adjusting a transmission strategy of the link, and optimizing load balance and a link priority of a station in the data in real time. According to the invention, the influence on the service when the fault occurs is reduced, and the abnormal problem positioning efficiency is improved.

The invention discloses a method and a system for realizing data synchronization between heterogeneous databases based on logs. The method comprises the following steps: acquiring connection information of a source database and a target database; querying a table structure of the source end database and generating an SQL statement to establish a data mapping rule; matching a corresponding rule model from a mapping rule model library; if the matching is not successful, the system abnormally quits and prompts the user to create a new mapping model and add the new mapping model to the mapping rule model base; converting a table structure of the source end database into a JSON character string based on a standard field type; an SQL statement required by the target database is output through the data mapping engine module; the message monitoring program reads the data in the temporary storage area and converts the data into data meeting the requirements of the target database; formatting the converted data into SQL statements supported by a target database; and sending the generated SQL statement to a target database to complete data migration. Accurate and controllable synchronization of the data and the model in a heterogeneous environment is realized.

The invention discloses a question and answer method and system based on tool calling, electronic equipment and a storage medium. The method comprises the steps that a user question and answer interface obtains question information of a user and sends the question information to a service layer; the tool retrieval module screens out IDs of candidate tools from existing tools according to the question information to obtain a candidate tool list; the tool calling module calls a large language model based on the candidate tool list and the question information; the big language model screens out an ID of a target tool associated with the question information from the candidate tool list, and generates a tool calling instruction based on the ID of the target tool; the tool calling module calls a target tool according to the tool calling instruction and obtains output parameters of the target tool; and the tool calling module calls a large language model to generate reply content based on the output parameters and the question information. The candidate tools are screened out through the tool retrieval model, then the large language model is called based on the ID of the candidate tools and the question information to determine the target tool, and the accuracy and comprehensiveness of reply content can be improved.

The invention provides a post quantum cryptography and national cryptography algorithm mixed signature and verification method and device, and relates to the technical field of cryptography application. The method comprises the following steps: performing hash operation on a to-be-signed message plaintext by adopting a preset national cryptographic hash algorithm to obtain a first hash value, and performing mixed signature operation on the first hash value and the to-be-signed message plaintext according to a national cryptographic signature private key component and a post-quantum signature private key component in a mixed signature private key of a sender to obtain a second hash value; and obtaining a national secret signature value and a post-quantum signature value, packaging the national secret signature value and the post-quantum signature value to obtain a mixed signature value corresponding to the to-be-signed message plaintext, and sending the mixed signature value and the to-be-signed message plaintext to a receiver. Due to the fact that the mixed signature value sent by the sending party to the receiving party comprises the national secret signature value and the post-quantum signature value, an attacker needs to crack the national secret signature value and the post-quantum signature value at the same time to achieve identity anti-fake attack, and guarantee is provided for integrity and authenticity of message plaintext transmission.

The invention discloses an AIGC multi-mode audio-visual content creation method and system, and belongs to the technical field of multi-mode audio-visual content generation and automatic creation, the AIGC multi-mode audio-visual content creation method comprises the following steps: an input module for inputting text description and materials required by creation by a user; the AIGC generation module is used for converting the text description and the material input by the user into a video sequence and a music clip; the multi-modal fusion and alignment module fuses and aligns the generated video sequence and the music clip to obtain an audio / video; the video intelligent editing module is used for splicing the segments of the audios and the videos and keeping visual coherence and smooth connection between the two audios and the videos; and the output module is used for outputting the generated audio and video as the media format required by the user. The method solves the problems that in the prior art, multi-modal audio-visual content creation lacks the ability of cross-modal cooperative work, the content generated during multi-modal information fusion and alignment is inconsistent in rhythm, semantics and emotion, the support of a later editing process is lacked, the content connection is not natural enough, and the creation speed is low.

The invention discloses a large model knowledge base construction method based on multi-granularity retrieval. The method comprises the steps of obtaining a target text and analyzing a document structure, splitting and reorganizing text data according to three levels of titles, fragments and sentences, and constructing three levels of knowledge of the titles, the fragments and the sentences; using a large language model to construct a generative index as question-level knowledge according to the sentence-level knowledge; using a vector model to generate a first vector representing index keys of fragment-level knowledge and / or sentence-level knowledge, and a second vector representing index keys of title-level knowledge and / or question-level knowledge; and respectively storing the first vector and the second vector into a vector database, and storing the index values and the index types corresponding to the first vector and the second vector into a relational database. According to the method, multi-granularity document knowledge base construction is achieved, the expression modes of knowledge under different granularities are expanded, the accuracy of user query and knowledge matching is improved, and the problem that information is lost or incomplete in an existing method is solved.

The invention discloses a domain-adaptive retrieval enhancement generation method and system, and the method comprises the steps: carrying out the document analysis and semantic partitioning of a document through a semantic understanding model and a document rule, and storing document fragments; on the basis of the large language model and a preset question library, generating a question and disassembling the question; performing correlation evaluation and sorting on the initial retrieval results in combination with a retrieval technology; candidate content most matched with the cue words is screened out through a large language model, and question-retrieval fragments are scored and marked; performing fusion on the initial retrieval result and the scoring and labeling result to construct positive and negative samples, and constructing a supervised data set; and based on a preset loss function, utilizing the supervised data set to carry out supervised training on the knowledge semantic search model, replacing the RAG mixed search module, and carrying out continuous iteration. By means of the technical scheme, new domain knowledge and operation feedback data can be flexibly applied, and domain self-adaptive retrieval enhancement generation is achieved.

The invention discloses a knowledge and data fused chronic disease collaborative management method and system, and relates to the technical field of medical management. Comprising the following steps: generating a feature data set, processing the feature data set by using a feature gain modeling method, and generating an enhanced feature data set; dynamically generating a chronic disease comprehensive knowledge graph, performing node supplementation and weight optimization on the knowledge graph, and generating a specific knowledge sub-graph of the patient; carrying out multi-time sequence prediction by utilizing the specific knowledge sub-graph, and carrying out short-term and long-term trend prediction; a patient health track model is constructed through the state transition probability in combination with the prediction result; according to the dynamic risk labeling result of the health track model, the health state of the patient is comprehensively evaluated in combination with the specific knowledge sub-graph, and personalized management suggestions are generated according to the evaluation result. According to the collaborative management platform, cooperation between different medical institutions and medical staff can be promoted, information sharing and resource integration are realized, and the overall level of medical services is improved.

The invention provides a wind power plant monitoring image automatic analysis and fault prediction method, system and device and a medium, and the method comprises the following steps: 1, collecting image data, sound data, vibration data, SCADA system data and environment data of a wind power plant, and forming multi-modal data; step 2, carrying out preprocessing on the obtained multi-modal data; 3, extracting features from the preprocessed multi-modal data, and fusing the features to obtain fused features; step 4, performing fan fault diagnosis and prediction based on the fused features to obtain a fault diagnosis and prediction result; according to the invention, end-to-end training of fault type identification and severity evaluation is realized, the accuracy of diagnosis and prediction is improved, and the workload of manual processing is greatly reduced.

The invention provides a business process construction method combining a workflow engine and a dynamic form, which relates to the technical field of low-code platforms, and comprises the following steps of: establishing a data table according to a business, selecting and importing the data table in a code generation module, generating a basic code package, re-operating a main program compiling code package and loading the code package to a JVM (Java Virtual Machine) operating environment; creating a dynamic form on the basis of the entity class information of the code package through a visual form designer of the dynamic form module, and outputting dynamic form configuration in a JSON (JavaScript Object Notation) format; according to the method, the dynamic form and the process engine are combined, highly flexible business process design can be realized, a user can dynamically design the form and the process model as required to meet different business requirements, and the user-defined component can be designed according to a business data structure and common functions, so that the form can better adapt to a specific business scene, and the user experience is improved. And the user experience and the working efficiency are improved.

The invention relates to the technical field of water pollution management, and discloses a water pollution tracing method and device and electronic equipment, and the method comprises the steps: determining at least one problem point location according to a water quality monitoring value time sequence corresponding to each monitoring point location in a selected range region in a target river channel; according to the position of each problem point location and / or the water quality analysis sequence corresponding to each problem point location, determining at least one to-be-checked river reach in the target river channel; and determining a first pollution source corresponding to the target river channel according to the water quality monitoring value time sequence and the flow monitoring value time sequence corresponding to each discharge port in each to-be-checked river reach. According to the embodiment of the invention, through decomposition and correlation analysis of the water quality index monitoring value time sequence, the change rule of the water quality index at the problem point location can be deeply excavated, reliable data support is provided for water pollution tracing, and the water pollution tracing efficiency is improved in combination with segmented troubleshooting capable of narrowing the water pollution tracing range. And a reliable basis is provided for water pollution treatment.

The invention discloses a knowledge graph-based nursing corpus automatic creation method, and relates to the field of artificial intelligence technology and medical information processing, and the method comprises a multi-dimensional data acquisition stage, a knowledge graph construction stage, a corpus automatic generation and updating stage, and a corpus quality control and evaluation stage. According to the automatic corpus generation method driven by the knowledge graph, dynamic generation and real-time updating of corpora are achieved by constructing an ontology structure, a corpus generation template and an updating algorithm in the nursing field; through a deep learning model and a transfer learning technology, new nursing knowledge and a diversified information structure are continuously introduced into the corpus, and the diversity of corpus content is increased.

The invention provides a feedback pushing method and system based on background quotation data, and relates to the technical field of data processing, and the method comprises the steps: receiving a quotation request uploaded by a client, carrying out the semantic analysis, obtaining a commodity name keyword, carrying out the extension of the commodity name keyword, carrying out the standardization processing of a commodity attribute, and determining the feature of the commodity attribute; determining customer quotation preference features, and comprehensively obtaining multi-dimensional quotation request feature vectors; constructing a combined retrieval condition, extracting feature vectors of the target quotation data, performing weighting, performing screening through a multi-criterion decision model, generating a comprehensive matching degree matrix, and performing screening to obtain high-quality target quotation data; and sorting, determining optimal quotation data, pushing the optimal quotation data, receiving feedback information and feedback scores, if the feedback information is acceptance, generating corresponding order information and sending the order information to a supplier, and if the feedback information is rejection, pushing the optimal quotation data again.

The invention discloses an auxiliary code review method and system based on a large language model, and the method comprises the steps: analyzing a submitted code file based on a static analysis technology and an abstract syntax tree AST extraction tool, and extracting key elements; reviewing the code through a pre-constructed company internal and external knowledge base by relying on a knowledge graph technology to obtain a reviewing result; performing context analysis on the code by adopting a large language model to obtain an analysis result; integrating the review result and the analysis result, and generating a review report through NLP; a containerization technology is adopted to be integrated with plug-ins of mainstream development tools, and private deployment is supported. According to the method, the efficiency, accuracy and safety of code review can be greatly improved, the workload of manual review is reduced, and automation and intelligentization of the code review process are realized.

The invention relates to a server application architecture migration method and device and a storage medium, and the method comprises the steps that an automatic detection module analyzes and checks a to-be-migrated application under an X86 architecture, and the to-be-migrated application is subjected to static code analysis, dynamic performance analysis and system compatibility check; according to analysis and check results of the automatic detection module, the automatic adjustment module replaces an X86 specific instruction and a library function, performs memory allocation optimization and memory mapping adjustment, and generates an automatic adjustment report; and the automatic optimization module executes a performance benchmark test, and executes memory access optimization, algorithm optimization, task scheduling optimization and multi-core parallelization adjustment according to a test result. According to the server application architecture migration method and device and the storage medium, the architecture adaptation process can be simplified, performance optimization support and automatic dependency relationship management can be provided, the migration efficiency can be improved, and the cost can be reduced.

The invention relates to the technical field of intelligent education, and discloses an integrated English teaching method and system based on artificial intelligence. The method comprises the following steps: constructing a digital resource library; generating pre-class preview data based on the resource library and the initial cognitive level of the student, analyzing the pre-class preview data and updating the cognitive level; generating classroom courseware based on the resource library and the student updating cognitive level, and analyzing classroom learning data to update the cognitive level again; generating personalized after-class homework based on the resource library and the re-updated cognitive level of the student, and analyzing homework data to finally update the cognitive level; and forming a heavy and difficult comment report based on the resource library and the final cognitive level of the student. Through continuous data collection and analysis, dynamic adjustment of teaching content is realized, pre-class preview, classroom teaching and after-class review are closely combined to form a complete teaching closed loop, teaching pertinence and effectiveness are improved, personalized learning and precise teaching are realized, and the overall effect of English teaching is greatly improved.

The invention relates to the technical field of servers, and discloses a silk-screen binding method, device and system for external card insertion equipment of a server, the method is applied to a processing module on a mainboard, and the method comprises the steps that the position of a PCIe expansion card in the server is obtained, burning information is read through an I2C switch of the PCIe expansion card, and the burning information is sent to the processing module; obtaining a physical slot silk screen of a server where the PCIe device is located on each slot, and obtaining an I2C address bound to each PCIe device; determining at least one PCIe device address according to a preset processor address, slot bandwidth information, at least one mapping relation and in-place information of the PCIe device on each slot; and establishing a binding relationship among the physical slot silk-screen of the PCIe equipment on each slot, the address of the PCIe equipment and the I2C address, and managing the PCIe equipment by using the binding relationship. According to the method, the BIOS or the BMC can freely access the same equipment through the I2C path, and the problem that specified equipment cannot be managed is solved.

The invention discloses a conflict detection processing method and system based on a BIM model, a medium and a product, and relates to the technical field of constructional engineering, and the method comprises the steps: obtaining a construction project design scheme; based on a preset model framework, determining a BIM model according to the construction project design scheme; predicting potential conflict points in the BIM model based on a preset conflict mode library; matching the potential conflict points with the building structure, the electromechanical pipeline and the equipment layout by using a space mapping algorithm, and determining possible conflict areas; on the basis of a natural language processing technology, operable solution suggestions are generated according to the possible conflict areas; after the operable solution suggestions are sent to the user, the solution suggestions determined by the user are received; and adjusting the BIM model based on the solution suggestion. By implementing the method, the accuracy and intelligence of conflict detection can be improved.

The invention provides a cross-platform low-code application development system based on a Flutter framework. Comprising a login registration module, a project management module, an interface design module, a state management module, a route management module, a team management module, a help document module, an AI page design module, a development document generation module, a hardware integration module, a code generation module, a multi-user collaborative development module, a communication module, an online simulator module, an AI generation application module and an interface management module. An asset management module, a developer forum module, an application market module and an application packaging module. The communication module supports various communication protocols and secure transmission modes, and ensures that data exchange applied to cross-platform and cross-system environments is secure and reliable. Through component dragging and graphical configuration, the low-code platform automatically analyzes configuration data to generate an App, a development document and a source code. And meanwhile, multi-person collaborative development is supported, so that the development threshold is reduced and the development speed is increased.

The invention provides double-arm picking equipment for shelf-type planted shiitake mushrooms and an operation method thereof. The double-arm picking equipment comprises a moving platform, the upper portion of the moving platform is connected with a chassis, and a lifting device, a shiitake mushroom storage device and a shiitake mushroom picking device are arranged above the chassis. Through mechanical automatic mushroom stick fixing and mushroom picking, intelligent identification, picking and placing of mushroom sticks on a shelf and identification and picking of mushrooms on the mushroom sticks can be carried out at the same time, planting areas can be traversed automatically, the mushroom picking speed is increased, and labor and time cost is saved. Three-dimensional scanning is carried out through the depth camera vision system, the position and size of the mushroom sticks and the maturity of mushrooms can be accurately recognized, and it is ensured that the quality of picked mushrooms is high. The lifting device adjusts the height of the mechanical arm and cooperates with a visual system, picking and mushroom stick processing are more accurate, damage to mushrooms and mushroom sticks is reduced, mushroom picking automation is achieved, operators do not need to put physical labor heavily, and the workload is relieved.

The invention discloses a multi-source modal data fusion-oriented charging pile fault diagnosis method and system. The method comprises the following steps of: acquiring message stream data, audio data and infrared sensing data associated with a charging equipment fault through a sensor system; and based on the characteristics of each modal data, fault characterization and identification are carried out by adopting a random forest, a convolutional neural network and a YOLO-v8 target detection model. According to the marked fault data, a mapping relation among multi-source data is established, and a Dempster-Shafer multi-source fusion theory is utilized to aggregate a multi-modal fault judgment result, so that the equipment fault is accurately diagnosed. According to the method, the accuracy of fault diagnosis and diversified presentation of fault types are effectively improved, the repair rate is reduced, and the method has a good engineering application prospect.

The invention discloses a real-time monitoring and early warning method for the leakage state of a long-line type public facility, and relates to the technical field of monitoring and early warning of the leakage state of the long-line type public facility, and the method specifically comprises the following steps: analyzing environment dynamic response information stored in a central monitoring system; respectively generating a soil humidity change coefficient, an environment pressure response index and a temperature influence compensation coefficient; constructing a leakage risk assessment model for the generated soil humidity change coefficient, the environment pressure response index and the temperature influence compensation coefficient, and generating a leakage risk coefficient; and determining a preset leakage risk coefficient threshold value, comparing the determined leakage risk coefficient threshold value with the generated leakage risk coefficient, evaluating whether a leakage risk exists in the pipe gallery area close to the earth surface, and respectively generating a normal signal and an abnormal signal according to an evaluation result. According to the invention, the problem of underground pipe gallery leakage monitoring is solved, abnormal signals are accurately distinguished, and the monitoring accuracy and safety are improved.

The embodiment of the invention provides a ship automatic berthing control method and system, electronic equipment and a storage medium, and belongs to the technical field of ship control. According to the method, motion state data of a current ship and a first relative distance between the current ship and a target berth are obtained, the motion state data and the first relative distance are input into a control strategy model for automatic berthing of the ship, and the ship control quantity at the next moment is obtained. The control strategy model is obtained through training based on a reinforcement learning algorithm, that is, environment interaction data is obtained, a target function is maximized, a value network is trained according to the environment interaction data, a strategy network is trained according to the value network and the environment interaction data, and the target function represents an accumulated reward value of an action output by the strategy network; the motion represents the ship control quantity, and then a control strategy model is determined according to the trained strategy network. According to the method, the workload of ship automatic berthing and leaving algorithm modeling can be reduced, the modeling precision is improved, and the safety of the ship automatic berthing process is improved.

The invention discloses a legal supervision clue mining method and system based on full-text retrieval and a large model, and belongs to the field of data collection and data retrieval and large model application. The method comprises the steps that S1, supervision rules and retrieval keywords are sorted; s2, full-text retrieval: carrying out data retrieval by utilizing keywords for supervising thematic sorting and a full-text retrieval system, and collecting all related image-text data in a specified time period from various data sources; s3, information distillation and information filtering; s4, constructing a knowledge base of thematic analysis; s5, searching and sorting the knowledge base; and S6, carrying out intelligent analysis and clue mining on the large model. According to the legal supervision clue mining method based on the image-text electronic data, basic data are collected through automatic keyword full-text retrieval, and valuable legal supervision clues can be mined from massive data through automatic element analysis and dialogue reasoning analysis of a large model, so that the legal supervision clue mining efficiency based on the image-text electronic data is improved.

The invention relates to the technical field of intelligent power grids, and discloses an abnormal power consumption behavior real-time monitoring and positioning method and system, and the method comprises the steps: carrying out the transformation of an existing collection device at an edge end, achieving the serial communication with the edge collection device, and carrying out the dynamic adjustment according to the collection condition and business demands of a transformer area, and forming a new collection strategy; clustering the electricity meters by using a Pearson's correlation coefficient and a DBSCAN clustering algorithm, dividing electricity meter clusters, and calculating the load condition of each cluster; according to the load condition and the acquisition weight of the electric meter cluster, the acquisition sequence and the acquisition frequency are adjusted, and the acquisition strategy is iterated and optimized periodically; and monitoring ammeter data in real time, identifying an abnormal electricity consumption behavior, and outputting an abnormal prompt. According to the invention, the algorithm is built in the edge computing platform through the big data algorithm analysis of the historical power consumption behaviors of the user, so that the dependence on manual judgment is effectively reduced, and the automation degree in the abnormal power consumption behavior monitoring, analyzing and processing process is improved.

The invention provides a self-adaptive network security early warning system and method based on deep learning, and aims to continuously update a threat recognition model through an advanced autonomous learning mechanism to adapt to a rapidly changing network environment. The system establishes a dynamic behavior baseline by integrating multi-source data including network traffic, system logs, user behaviors and the like, and realizes real-time monitoring of network behaviors and accurate identification of abnormal behaviors; once potential threats are detected, the system can automatically trigger preset response measures, such as suspicious traffic isolation and access request blocking, so that actions can be taken quickly before damage caused by the threats; according to the design of the system, the dependence on manual intervention is reduced, the real-time performance and effectiveness of early warning are improved, and the recognition accuracy of unknown attacks is remarkably improved; through the automatic and intelligent early warning mechanism, more reliable and intelligent protection is provided for network space security, and high efficiency and accuracy of network security management are ensured.