79results about How to "Live Update" patented technology

The invention discloses a CCER forestry carbon sink project development system based on artificial intelligence technology monitoring, and relates to the technical field of carbon sink monitoring and optimization. According to the CCER forestry carbon sink project development system based on artificial intelligence technology monitoring, space-time estimation is carried out on CCER forestry carbon sink project data through the deep learning model, and the dynamic change of the carbon sink amount is accurately predicted. Spatial features are extracted through a convolutional neural network, time sequence data are analyzed in combination with a long-short-term memory network, and a carbon sink prediction model is constructed. And through statistical analysis and a spatial interpolation algorithm, carbon sink quantity change is monitored in real time, an abnormal trend is identified, and early warning is provided. Based on a mixed integer linear programming algorithm, forest land resource allocation and vegetation types are optimized, a carbon sink optimization scheme is generated, and carbon sink benefit maximization is promoted. And through an intelligent carbon sink management scheme, sustainable ecological development and green and economic popularization are assisted.

The invention belongs to the technical field of unmanned aerial vehicle inspection, and particularly provides a photovoltaic power station inspection method and system based on an unmanned aerial vehicle and a GIS, and the method comprises the steps: obtaining initial geographic information data of a photovoltaic power station, enabling the unmanned aerial vehicle to execute initial surveying and mapping flight, collecting high-resolution image data, and constructing a three-dimensional model of the photovoltaic power station; fusing the high-resolution image data with the initial geographic information data to generate a multi-factor initial intelligent inspection path; the unmanned aerial vehicle flies along the initial intelligent inspection path, collects multi-modal data of the photovoltaic module, and transmits the multi-modal data to a GIS for data fusion and updating to obtain fused data; generating a fault distribution thermodynamic diagram and a maintenance priority map; the inspection path is dynamically adjusted, and the three-dimensional model of the photovoltaic power station is updated. According to the method and the system, comprehensive inspection can be carried out on the photovoltaic power station, the inspection accuracy and efficiency are improved, the inspection path can be dynamically adjusted, unnecessary repeated inspection is reduced, and the inspection cost is effectively reduced.

The invention discloses a data management system based on a monitoring video stream, belongs to the field of data analysis, and aims to solve the problems of camera connection acquisition, image quality optimization, pedestrian related information analysis and data storage retrieval and backup in video monitoring. The system comprises a data acquisition module, a target detection module and a data storage module. The data acquisition module is used for identifying and connecting a video monitoring camera, performing video stream data acquisition, adjusting an acquisition frame rate by estimating a data size, and evaluating and optimizing image quality to obtain a detection image data set; the target detection module is used for carrying out feature extraction, classification and marking on pedestrians in the detection image data set, recording pedestrian trajectory information, carrying out real-time tracking and updating, identifying a behavior mode according to the trajectory information, dividing a gathering area and obtaining the pedestrian flow; and the data storage module is used for classifying and labeling the data, constructing an index structure to guarantee efficient retrieval, dividing data grades according to multi-dimensional features, and dynamically adjusting a backup time interval.

The invention relates to a vehicle and unmanned aerial vehicle cooperative scheduling method based on hierarchical reinforcement learning, belongs to the technical field of traffic transportation and logistics, solves the problems of high cost, low efficiency and unreasonable resource allocation of'ground-air integration 'joint transportation in the prior art, and comprises the steps of S1, constructing an interactive simulation environment of urban rapid logistics transportation; s2, constructing a dynamic scheduling model of the vehicle unmanned aerial vehicle based on the co-scheduling process of the vehicle unmanned aerial vehicle by using r-MDP; s3, designing a hierarchical reinforcement learning algorithm framework, and solving the vehicle unmanned aerial vehicle dynamic scheduling model through the hierarchical reinforcement learning algorithm framework to obtain a cooperative scheduling strategy; and S4, substituting the obtained collaborative scheduling strategy into the constructed interactive simulation environment for verification to obtain a verification result, if the verification result meets a preset requirement, outputting the collaborative scheduling strategy for collaborative scheduling of the vehicle and the unmanned aerial vehicle, otherwise, returning to the step S3 to modify the parameters and reconstructing the hierarchical reinforcement learning algorithm framework.

The present invention relates to the field of geographic information system technology, and specifically to a flood simulation prediction system based on GIS data. The system includes: a data integration module collects climate and geographic information at the basin scale, regional scale and global scale, performs data verification and format standardization, integrates into a unified data set, extracts multi-regional climate trends and geographic features, constructs indexes, and generates a geographic climate database. In the present invention, a geographic climate database is constructed by integrating data of various scales and performing standardized processing, improving data consistency and availability, finely adjusting model parameters, optimizing model structure according to regional specific climate and geographic features, and enhancing the adaptability and accuracy of the prediction model. In addition, state transition data is used to calculate future flood risks, provide dynamic risk assessment, and update flood probability and intensity information in real time, making flood risk management more forward-looking and practical.

The invention relates to the technical field of medical rehabilitation, in particular to a rehabilitation guidance method and system based on an exercise prescription. Comprising the following steps: S1, acquiring an exercise prescription sent by a doctor to a patient, and establishing a body model according to the real body state of the patient; s2, extracting prescription contents in the exercise prescription according to different rehabilitation stages, and inputting the prescription contents of the same stage to the body model according to the rehabilitation stage of the patient to perform repeated rehabilitation simulation so as to obtain simulated body states of various different results of the corresponding rehabilitation stage of the patient; through the difference extraction of the body model before and after updating, the change of the body of the patient can be accurately known, the exercise prescription is ensured to be adjusted according to the current body condition, the pertinence and effectiveness of rehabilitation treatment are improved through the personalized adjustment, the exercise prescription is recommended in combination with the feedback data of the patient, the treatment scheme can be updated in real time, and the rehabilitation effect is improved. And the method adapts to actual progress and feedback of patients, so that the treatment effect is optimized.

The invention discloses an advertisement pushing method and device based on artificial intelligence and a medium, and relates to the technical field of advertisement pushing, and the method comprises the steps: collecting data information of a user, carrying out the preprocessing operation, and dividing the data into a scene data set and a user interest data set; constructing a scene recognition model, and training the scene recognition model through the scene data set; constructing a user interest model, and training the user interest model through the user interest data set; analyzing the advertisement content, extracting an advertisement keyword, defining a scene keyword for the scene according to the current scene of the user, and matching and pushing the scene keyword; and carrying out effect evaluation and optimization on the pushed advertisement. According to the method, advertisements related to the current scene can be pushed to the user through scene perception advertisement pushing, so that the click rate and the conversion rate of the advertisements are improved, the satisfaction degree of the user is improved, and the loyalty of the user to the brand is enhanced.

The invention discloses an online identification method for kinetic parameters of a joint type series robot, which comprises the following steps: S1, for a to-be-identified joint type series industrial robot, establishing a robot kinetic model considering friction; s2, linearization is carried out on the joint type series industrial robot dynamic model; s3, designing an optimal excitation track for an identification experiment, and obtaining an excitation track by using five finite Fourier series and solving a constrained nonlinear optimization problem; and S4, the series robot runs the excitation track, meanwhile, the position information of each joint of the robot and the driving current of each joint at each moment are collected, and to-be-identified parameters are calculated on line at each moment. According to the method, online identification of the robot kinetic parameters can be carried out, the identification efficiency of the robot kinetic parameters is improved, and the method can be used for industrial scenes such as robot moving and carrying, polishing and grinding and heavy-load hydraulic pressure.

The invention discloses a data security document generation method and system based on an RAG technology, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out isolation processing on data security related data based on data source information; storing the encrypted data and the unencrypted private data into a private data security database, and updating the mass data security vertical industry data into the private data security database in real time; in response to a generation request of the data security document, extracting a keyword corresponding to a user demand, and performing similarity retrieval in the private data security database based on the keyword to obtain corpus data having the highest similarity with the keyword; and the corpus data, the user demand and the final document template are jointly input into the large language model to generate the data security document, so that the efficiency and accuracy of generating the data security document are improved.

The invention discloses a mobile phone information privacy protection method and system based on big data analysis, and relates to the technical field of information security, and the method comprises the steps: collecting latest privacy protection requirements from an application market and / or a supervision department, extracting privacy protection terms, and generating a standardized privacy protection rule data set; after an encryption analysis result is obtained, a dynamic privacy protection rule file is generated in combination with big data analysis; for the dynamic privacy protection rule file, analyzing byte codes of a mobile phone application through an ASM framework, automatically modifying a sensitive API calling point, and inserting privacy monitoring logic; repackaging the modified sensitive API calling point into an APK file, and carrying out privacy monitoring verification on the application program; according to the method, encryption analysis and distributed training are adopted, safe sharing and processing of privacy data under participation of multiple parties are ensured, the protection strength of mobile phone information privacy is effectively enhanced, and the method is suitable for complex and changeable application scenes.

The invention relates to the technical field of semiconductor test equipment, in particular to a full-automatic high-precision probe station, which utilizes multi-physics field coupling sensing and compensation to remarkably improve the positioning precision: by comprehensively collecting multi-physics field data such as a temperature field and a stress field and combining a coupling algorithm to optimize a compensation strategy, multi-factor interference is effectively counteracted, and the accuracy of the probe station is improved. The positioning repetition precision can reach + / -0.05 [mu] m, and the test requirement of the advanced semiconductor technology is met; a dynamic three-dimensional modeling technology and dynamic adaptability enhancement are achieved, a dynamic three-dimensional modeling system with the size affected by multi-physical field data can update the form of a test target in real time, test deviation caused by target deviation or surface fluctuation is avoided, and the adaptability of equipment to a complex test scene is improved. The automation degree is high, the testing efficiency is improved, the whole process of data acquisition, modeling, compensation and testing can be completed without manual intervention, the calibration process is simplified, the testing period is shortened, and the method is suitable for batch detection scenes.

The invention relates to the technical field of evaluation systems, in particular to an evaluation system and method based on business personnel and clients, and the system comprises a data collection module which is used for collecting the position information, daily behavior data, access data and client interaction records of the business personnel; the customer big data management module is used for collecting, storing, analyzing and managing interaction data, customer behavior data and demand data between business personnel and customers; the data analysis module preprocesses the data of the customer big data management module and the data acquisition module, and identifies the behavior pattern of business personnel and customer demands; the strategy control module carries out strategy reporting and reporting reminding according to the data analysis result, and optimizes the working process of the business personnel; and the execution module performs automatic reporting, data reporting and reminding sending according to strategy control. According to the method, data relevance between business personnel and clients is analyzed, mode clustering analysis is carried out on the business personnel and the clients, and an evaluation system of performance of the business personnel is constructed.

The invention relates to the technical field of intelligent mine mining, in particular to an intelligent mine physical property parameter real-time inversion and coal mining simulation real-time optimization method. The method specifically comprises the steps of arranging monitoring points, and monitoring physical property parameter stress data sigma and displacement data u in real time; establishing a mathematical model composed of a geometric equation, an equilibrium equation, a constitutive equation and initial-boundary conditions; a solver is used for simulating the coal mining process, and simulated stress data sigma simulation and displacement data u simulation of each monitoring point are obtained; comparing the real-time simulation stress data sigma simulation and the displacement data u simulation of each monitoring point with the field real-time monitoring stress data sigma monitoring and the displacement data u monitoring, and constructing a loss function; and by utilizing an optimization algorithm, the physical property parameters of the stratum are determined while the coal mining simulation is more accurate. According to the method, the accuracy and optimization effect of coal mining simulation can be improved, so that the safety and resource utilization rate of mine mining are improved.

The invention discloses an equipment state evaluation method based on energy data, which overcomes the problems that a user cannot obtain effective information from energy data and cannot accurately evaluate the equipment state in the prior art, and comprises the following steps: collecting energy data, and preprocessing the collected energy data; according to a preset energy data archiving model, matching the collected energy data to obtain an energy holographic archive, and establishing an energy data asset tree and a data processing rule; based on the energy holographic archive, extracting equipment indexes according to energy consumption characteristics, and constructing an energy holographic archive index system; and evaluating the equipment state according to the index system. By establishing the holographic file and extracting the equipment indexes according to the energy consumption characteristics, the user can more comprehensively understand and utilize the energy data, the accurate evaluation of the equipment state is realized, and more comprehensive and accurate information support is provided for the development of the equipment.

The invention provides a system and a method for intelligent management of energy and computing equipment, which are used for management of energy data. The system is of a four-level architecture and comprises a first level, a second level, a third level and a fourth level, and the first level is responsible for data storage, processing and analysis; the second hierarchy adopts a data transmission method, and data transmission is carried out between the first hierarchy and the third hierarchy; the third level performs data transmission with the second level through an uplink communication interface, performs calculation and management of energy data by using an edge calculation device, and performs data transmission with the fourth level through a downlink communication interface; and the fourth level performs data acquisition through an energy monitoring terminal. According to the technical scheme of the invention, the method has the advantages of high compatibility and expansibility, real-time updating of the monitoring data, improvement of the energy management and control level, substantial improvement of the user experience, realization of rapid fault positioning and recovery, optimization of resource configuration, cost saving and energy consumption reduction.

The invention discloses an on-chain enterprise risk identification method and system based on a credit chain large model. The system comprises a data preprocessing module, a model matching module, a weight parameter loading module, a data operation reasoning module, a risk prediction output module and the like. Large model training and optimization are carried out by integrating industry, region, type and other multi-dimensional data sets, a credit chain vertical type general model and a special model are formed, and the method can adapt to credit and risk prediction evaluation, monitoring and early warning of a single enterprise or an integrated enterprise in different supply chain and industry chain scenes. A more comprehensive, accurate and real-time solution is provided for enterprise management and industry supervision, and remarkable beneficial effects and advantages are achieved.

The application provides a kind of intelligent government affair question and answer method, comprising the following steps: S1, government affair file is used to build government affair knowledge base and question and answer data set;S2, through the instruction following function in open source model, ask the knowledge base file, generate government affair question and answer training data;S3, through the pre-training language model of well-trained, based on the policy problem of user query, from the government affair knowledge database, the relevant policy file is matched in coarse granularity;S4, the policy file is cut into policy paragraph, and the question and policy paragraph are input into the pre-training language model of well-trained, guide model and the most relevant policy paragraph of question match;S5, the question and policy paragraph are constructed into prompt, and the prompt is input into the large language model of well-trained, guide the large language model of well-trained to generate the answer of question.The application can achieve diversity generation on the basis of accurate answer, and users can ask the policy content they care about, and obtain the answer of the latest policy content in real time.

The invention discloses a data sharing method based on multi-tenant isolation, and relates to the field of tenant data sharing, and the method comprises the following steps: collecting the personalized information and house renting information of tenants; setting a multi-tenant cellular network, and performing multi-tenant cellular network planning on the tenants according to the personalized information of the tenants to obtain exclusive grid codes of the tenants; a sharing authorization list of the tenants is set, and according to the sharing authorization list, the sharing tenants carry out sharing requests and sharing behaviors on the shared tenants; the multi-tenant cellular network after data sharing is subjected to data checking and data updating, the isolation and privacy of tenant information are improved, the efficiency and safety of data sharing between tenants are improved, multi-tenant data are efficiently managed, the utilization rate of the data is increased, and the requirements of the tenants for data safety and privacy are met.

The invention discloses a benefit analysis method and system considering distributed adjustable resource multivariate subjects. The method comprises the following steps: analyzing the operation characteristics of a multi-element subject, the multi-element subject comprising a new energy power generator, an energy storage operator, a thermal power generator and an electricity buyer, and establishing a quotation decision model based on a reputation value according to the reputation value and the operation characteristics of the multi-element subject in the electricity transaction; solving the quotation decision-making model through a multi-objective evolutionary algorithm to obtain clearing electric quantity and clearing electricity price, establishing benefit evaluation indexes according to the comprehensive income of the multi-element main body, the output proportion of the new energy main body, the user peak-valley difference and the energy utilization rate, and calculating weight vectors of a plurality of benefit evaluation indexes by using a game theory combination weighting method; and weighing the benefit evaluation indexes through a multi-criterion optimization and compromise solution method to obtain a comprehensive benefit analysis result of the multivariate subjects. According to the scheme, decision scientificity and fairness are improved.

This invention relates to the fields of artificial intelligence, multi-agent collaborative scheduling, and federated security management. Specifically, it is a federated capability management and unified scheduling system for multi-agent collaboration, comprising: a central scheduler receiving collaborative task requests across multiple local agent nodes and obtaining capability declaration information containing only the capability tags of the local agent nodes; constructing prompt word templates and generating an initial fine-grained task decomposition scheme; extracting cross-domain call links, statistically analyzing the frequency of cross-domain calls and data interaction dimensions, predicting the communication interruption probability of local agent nodes and comparing it with a security risk threshold; if the probability is lower than the threshold, a fine-grained scheme is adopted; if the probability is higher than or equal to the threshold, a minimum-privilege interaction coarse-grained scheduling scheme is generated and distributed; and local agent nodes executing sub-tasks and reporting their status to maintain core business continuity without exposing underlying private data.

The present invention discloses a method, system and storage medium for constructing a target object portrait, which is applied to the field of information technology and can dynamically update the target object portrait in real time and effectively improve the accuracy of the target object portrait. The method includes: analyzing the target object's use behavior events and constructing behavior event data; wherein the behavior event data includes a number of target object behavior events; creating a first behavior tree according to the behavior event data; wherein the first behavior tree includes a number of behavior nodes, and the behavior nodes correspond to the target object behavior events; obtaining the target object behavior data through a preset event-driven model, so as to update the first behavior tree according to the target object behavior data and generate a second behavior tree; and constructing the target object portrait by analyzing the second behavior tree.

The invention relates to the technical field of database information, in particular to a method for generating extensible multi-type database structure documents, which is a method for generating different types of data source structure documents through configurable data source types aiming at a multi-type data source adaptation and database table structure analysis technology. A user only needs to newly add data source connection information and test connection success, and only needs to provide data source related information and a file type HTML or word needing to be generated when a database structure document is checked or generated; in addition, according to the method, a document template needing to be exported can be configured according to a database table of the user, the document is automatically generated, and incompleteness and mistakenness of handwritten documents are avoided.

The present application belongs to the technical field of port safety monitoring, and specifically relates to a method and system for identifying personnel approaching a cable launching area in a port, a terminal and a storage medium, which comprises selecting a fixed cable column of a port berth as a physical reference, using a high-resolution network camera to collect panoramic images of the port berth, using a pre-trained YOLOv8 deep learning model for multi-target segmentation, and performing secondary focusing identification to quickly and accurately identify personnel, cables, cable columns and ship outline targets, and by obtaining dynamic factors such as cable tension and ship docking angle, the reference radius of the dangerous area is corrected by combining the corresponding calculation formula, and a dynamic dangerous area polygon is generated, fully considering the dynamic changes of the port operation environment, which can update the dangerous area in real time, making the division of the dangerous area more in line with the actual situation, avoiding misjudgment and missed judgment due to the fixed dangerous area, and improving the accuracy and effectiveness of safety management.

The invention discloses a control system and a control method for 3D hard metal processing equipment, and the system comprises a processing unit which is configured to receive data from a sensor; the storage unit is used for storing a preset processing parameter set; the algorithm module is used for executing weighting calculation so as to dynamically adjust parameters in the processing parameter set based on the physical characteristics; and the output interface is used for transmitting the adjusted processing parameters to an execution mechanism of the 3D hard metal processing equipment. According to the invention, the data from the sensor can be received, and the processing parameters can be dynamically adjusted according to the data, so that the processing process is optimized. By introducing a weight distribution unit and weighting calculation based on historical data, the flexibility and adaptability of the system are improved, and the machining quality and efficiency are ensured. In addition, the user-friendly interface design enables the user to conveniently input or select the type of the to-be-processed material and the expected processing effect, and the usability and flexibility of the system are further improved.

The invention discloses a data management system for metallurgical electromechanical construction, and belongs to the technical field of metallurgical electrical construction management. The system comprises a data analysis module, a data processing module, a data entry and update module and a data display module. The data analysis module is used for acquiring data related to metallurgical electromechanical construction, screening the data to obtain target data, and preprocessing the target data to construct association rules, and the data processing module is used for performing data analysis on construction process data according to the association rules, generating analysis data, and sending the analysis data to the data processing module. The data recording and updating module is used for recording the analysis data into a pre-established table so as to store the analysis data, and the data display module calls the analysis data recorded in the table and displays the analysis data. The system has efficient data processing capability, and construction data can be input, updated and analyzed in real time.

The invention relates to a natural resource two-dimensional and three-dimensional integrated service system and method, and belongs to the technical field of geographic information, and the natural resource two-dimensional and three-dimensional integrated service system comprises a storage module, a service module, a business module and a rendering module. The storage module is used for storing two-dimensional data and three-dimensional data of natural resources and providing a data access interface; the service module is used for classifying and processing the two-dimensional data and the three-dimensional data and providing a service interface; the business module is used for calling a service interface so as to integrate data services of the service module and provide efficient data; and the rendering module is used for calling the efficient data to construct a two-dimensional and three-dimensional data model, and converting the two-dimensional data and the three-dimensional data into a visual interface based on the two-dimensional and three-dimensional data model, so that the rendering performance is improved.

The present invention discloses a method for predicting silicon content in molten iron based on TD-LightGBM, and belongs to the technical field of industrial process monitoring. The method comprises: first, using the decision tree model structure of a lightweight gradient booster to judge the importance of the feature according to the number of times the feature is used to segment training data; then, combining a time difference algorithm to establish a dynamic feature extraction model; finally, using a local weighted algorithm to establish a local model based on the Euclidean distance between samples. Predicting the silicon content in molten iron during the ironmaking process based on this model can effectively remove redundant items and drift phases in the blast furnace environmental parameters. Compared with the existing prediction scheme for silicon content in molten iron, the present invention further improves the accuracy of the prediction.

The present application proposes a joint knowledge graph heat ranking method and device, which relates to the field of information processing technology, wherein the method includes: obtaining a preset number of paper documents, performing entity recognition on the paper documents, and extracting target entities from the paper documents; extracting relationship attributes and entity attributes from the target entity, and constructing a knowledge graph based on the relationship attributes and entity attributes of the target entity; obtaining a comment text containing the target entity, and constructing an entity link with the knowledge graph based on the entity relationship contained in the comment text; determining the entity heat value based on the word frequency-inverse text frequency index value of the linked target entity and the comment text, and updating the heat attribute of the target entity in the knowledge graph based on the entity heat value. The present invention constructs a knowledge graph by extracting entities in paper documents, and predicts the heat attribute values ​​of entities in papers based on paper comments, and scientifically and reasonably gives entity heat rankings to correctly and accurately implement entity content recommendations, and can update the heat attribute values ​​of entities in real time.

The invention discloses a video matrix switching method and circuit, electronic equipment and a storage medium, and relates to the technical field of video switching control, and the method comprises the steps: obtaining a target input source of a switching instruction in response to the switching instruction of a data transmission module through a control module connected with a switching matrix module and the data transmission module; an original input source is selected from the multiple input sources of the switching matrix module, and the original input source is any one of the multiple input sources currently output to the video matrix by the switching matrix module; and controlling the switching matrix module to switch the original output port corresponding to the original input source in the current output to the video data input by the target input source. According to the method and the device, the display content of the video matrix can be quickly, accurately and automatically updated, and the video needing to be switched can be timely output to the video matrix in an emergency.

The present invention provides an agricultural product traceability identification method based on the Internet of Things, which comprises the following steps: receiving a remote viewing location selected by a user terminal in an agricultural product purchasing area, acquiring record data collected by a monitoring device based on the remote viewing location, filtering multiple image frames corresponding to the record data according to an image filtering model, obtaining a customized set corresponding to the user terminal, obtaining a purchasing condition input by the user terminal, performing condition matching analysis on the customized set according to the purchasing condition, obtaining purchasing recommendation data and sending it to the user terminal, obtaining sorting monitoring data corresponding to a sorting terminal according to the purchasing data of the user terminal, generating traceability data according to the sorting monitoring data and sending it to the user terminal.