1461 results about "Data matching" patented technology

The invention discloses a substation equipment rare defect simulation and identification method and system and a storage medium. The method comprises the following steps: constructing an equipment reference feature library; marking dynamic features of rare defects in historical inspection according to a spatial-temporal feature enhancement algorithm, generating a knowledge graph, and constructing a dynamic defect learning library; the method comprises the following steps: learning space association and environmental factor influence of defects and equipment through a bimodal generation network, and generating initial defect data matched with a weak area of the equipment; generating high-credibility defect fusion data through physical constraint-intelligent detection double screening; constructing a three-dimensional mixed data set, and screening high-quality training samples through a dynamic defect evolution algorithm and hierarchical cognitive evaluation; and constructing a multi-algorithm collaborative fine tuning network by using a federated learning framework, simulating and labeling defect information, and outputting a multi-dimensional identification prediction report. The method aims at solving the problems that the model is insufficient in rare defect recognition precision and lack of evolution prediction ability, and high-quality simulation of rare defect samples and high-precision recognition of the model are achieved.

The invention relates to a psychological counseling interaction method and device based on an autonomous psychological planning architecture. The method comprises the following steps: acquiring initial user data of a target user; constructing a dynamic target map of a target user through a three-layer nested target structure, and pre-loading a matched personalized decision tree; after receiving the real-time interaction data, executing real-time path re-evaluation based on the real-time interaction data to obtain a treatment value function of each intervention path; constructing an intervention response prediction model by adopting a Bayesian network and a Monte Carlo tree search algorithm, adjusting the priority and the execution sequence of the intervention paths in the personalized decision-making tree in combination with the treatment value function of each intervention path, and selecting a target intervention path matched with the real-time interaction data from the adjusted intervention paths; the real-time interaction data is mapped into the multi-dimensional psychological state space to serve as the session trajectory, session trajectory planning is conducted based on the target intervention path, real-time interaction with the target user is achieved, and the accuracy of intervention decision making and the session fluency are improved.

The invention relates to a data lake-based industry templated modeling and dynamic access control method, which comprises the following steps of: acquiring multi-source heterogeneous data of a data center in real time, and performing data verification, key field extraction and metadata extraction through an analyzer; according to the data classification and grading key points, grading protection is carried out on the currently obtained data matching industry grading and classification template, and the protection grade is dynamically adjusted according to the data dynamic access control rule, the sensitivity and the service importance; performing threat detection and risk prediction on the abnormal behavior data by using a machine learning algorithm; constructing a distributed intelligent data lake storage architecture, and storing the currently acquired data into a data lake in a layered manner according to a classification result; and displaying the security situation and the early warning information through a visual interface. The invention also relates to a corresponding system. By adopting the industry templated modeling and dynamic access control method and system based on the data lake, the limitation of traditional data lake modeling is effectively solved.

The invention provides a tunnel event and warning lamp acousto-optic linkage strategy generation system based on AI decision, and relates to the technical field of intelligent traffic, and the method comprises the steps: collecting tunnel traffic event data, vehicle structured data, vehicle coordinates, vehicle flow, vehicle speed, and brightness data inside and outside a tunnel in real time, so as to obtain multi-source heterogeneous data; according to the multi-source heterogeneous data, taking the data matching degree, the space-time consistency and the event confidence as multi-objective optimization dimensions, constructing a weighted objective function, generating a Pareto optimal solution set through a multi-objective optimization algorithm, screening the solution set based on space-time constraint conditions, and removing conflict hypotheses; and determining the final event type and the structured event description of the three-dimensional geographic coordinates. The problems of large illumination energy consumption and poor system linkage in existing tunnel safety management are solved.

A blockchain-based system for managing music rights and royalties is disclosed. The system enables artists and contributors to upload music, assign revenue percentages, and track usage via smart contracts on a distributed ledger. Play counts are immutably recorded across distributor platforms. A contributor dashboard provides real-time access to royalty data. The platform incorporates Majority Reports to validate metadata matches and calculate royalties, and Minority Reports to flag discrepancies without payments, thereby ensuring data integrity. A Golden Box smart contract module replicates song rankings and applies predictive classification models to identify features associated with musical success. These mechanisms improve transparency, accuracy, and fraud prevention in royalty distribution.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of data center operation and maintenance, financial science and technology, medical treatment and health and the like, and discloses a task processing method and device based on a domain knowledge base, equipment and a medium. Cleaning and formatting to generate standardized task list data, inputting the standardized task list data and a domain knowledge base into a language model to generate structured task list data, and matching task list types based on the structured task list data to generate a task list execution plan, and determining an execution mode according to the task list execution plan and executing to generate a task list execution state. Through cooperative processing of the domain knowledge base and the language model, standardized and structured processing of task list data is realized, and in combination with task type matching and execution mode control, processing automation and accuracy are improved, manual participation is reduced, and response speed and efficiency are improved.

In some examples, a system monitors input / output (I / O) operations to identify data matching a honeypot pattern. The system determines storage location information associated with the data identified as matching the honeypot pattern, and detects an access of the data at a storage location indicated by the storage location information. The system indicates a potential attack based on detecting the access of the data at the storage location indicated by the storage location information.

The invention relates to a tunnel surrounding rock three-dimensional deformation monitoring system integrating monocular vision and millimeter wave radar. The tunnel surrounding rock three-dimensional deformation monitoring system comprises in-tunnel sensing equipment, a tunnel opening terminal, a database and application server and a remote monitoring end. The invention also relates to a tunnel surrounding rock three-dimensional deformation monitoring method fusing monocular vision and millimeter wave radar. The method comprises the following steps: S1, setting a monitoring target; s2, multi-modal data acquisition is carried out; s3, visual and radar target detection; s4, performing visual and radar heterogeneous data matching; s5, solving pixel displacement and radial displacement; s6, calculating the three-dimensional deformation of the surrounding rock; and S7, alarm judgment and result output. According to the invention, the precision, the real-time performance and the automation level of tunnel surrounding rock deformation monitoring can be obviously improved, and the method is especially suitable for scenes with complex environment and high safety risk in the early stage of tunnel excavation; the invention aims to provide an efficient, accurate and automatic monitoring means capable of adapting to the early stage of excavation for tunnel surrounding rock deformation.

The invention discloses an emergency patient information data matching method and system based on the Internet, and the method comprises the steps: obtaining multi-source heterogeneous data in real time according to an electronic medical record, image data and real-time vital sign data of an emergency patient, and generating a time-synchronized multi-source data set through a self-adaptive data format conversion algorithm; for the multi-source data set, using a feature extraction network to extract illness state features of patients, and generating patient priority scores; adjusting a resource allocation scheme in real time by adopting a medical resource matching algorithm based on a graph neural network according to the patient priority score and the illness state feature, and generating a preliminary medical resource matching result; and for a medical resource matching result, generating a final emergency patient information data matching scheme through a differential privacy protection mechanism by adopting a data security transmission protocol based on homomorphic encryption. According to the embodiment of the invention, the method can meet the requirements of quick, safe and effective processing of data in an emergency scene, and improves the quality and efficiency of emergency medical service.

The invention relates to the technical field of state monitoring, in particular to an energy-saving air compressor running state monitoring system and method, and the system comprises a pressure slope analysis module, a deviation trend judgment module, an error fitting acquisition module, an error trend analysis module and an alarm triggering module. According to the method, a pressure range is calculated by dividing time slices, a slope ratio is generated, a dynamic threshold algorithm is combined to successively compare and capture an offset trend, frequency and current waveform data are synchronously acquired to match a timestamp to calculate a difference value, an error vector is generated in a standardized manner, and a periodic mean value is extracted to verify an incremental relationship to identify progressive anomaly. The cross validation slope ratio and error vector positioning wear or coordination abnormity, the dynamic threshold value is adjusted along with the mean value coefficient at the initial period to reduce fluctuation interference, the timestamp matching enhances the composite fault detection capability, and the range division operation quantifies the matching degree to provide an energy efficiency optimization basis. And a standardized error vector and mean value incremental mechanism improves the prediction precision and reduces false alarm and missing alarm.

The invention relates to the technical field of data processing, can be applied to business scenes such as financial science and technology, medical treatment and health, and discloses a data matching method based on security approval, which comprises the following steps: creating a data table and configuring access authority, inserting data in the table into an acquisition table and then synchronizing to an intermediate database and adding a field identifier; synchronizing the data of the intermediate database to a distributed storage structure partitioned according to dates through a timed task; receiving a data table name, a data type and identification information, determining a matching field based on the data type, matching the data value in the distributed storage with a target field, and generating a result set; and submitting a matching result as a security signature, triggering an approval process, and sending result data to the terminal according to permission mapping after approval is passed. According to the method, the data processing efficiency is improved and the sensitive data circulation risk is reduced by constructing the structured acquisition process, setting the automatic synchronization mechanism, executing data matching based on the field type and integrating the approval control logic.

The invention provides a trade whole industry chain data intelligent matching and resource docking method, and relates to the technical field of international trade data analysis and geographic information systems.The method comprises the steps that customs declaration data, logistics tracking data, enterprise supply chain data and market public opinion data are collected in real time through a standardized interface; constructing a multi-source heterogeneous data fusion system of block chain evidence storage; dynamically modeling a whole industry chain relation network based on the knowledge graph, and quantifying the supply chain dependency, the trade flow direction and the policy influence weight; calculating an industrial chain correlation index ICRI and a resource matching priority coefficient RMPC, optimizing a logistics path in combination with a geographic space analysis algorithm, and avoiding a policy restriction area in real time; and rendering a matching result through a three-dimensional visualization platform, and iteratively updating model parameters based on user interaction feedback. According to the method, the limitation of a traditional data island is broken through, dynamic quantitative analysis and accurate resource matching are realized, and the trade data integration efficiency is remarkably improved through intelligent path planning and interactive decision support.

The invention discloses a composite precipitation cloud layer identification method based on a laser radar-cloud radar, and the method comprises the steps: obtaining the observation data of the laser radar and the cloud radar, and carrying out the data matching of the observation data; processing a signal of the laser radar in a height interval of 18-20 km to obtain a preprocessed laser radar signal; performing laser radar cloud boundary identification based on a VED algorithm, and endowing different laser radar cloud scores according to the signal attenuation rate and the signal gradient; removing earth surface clutters by using a threshold method based on observation of spectral width and Doppler velocity; carrying out cloud radar significant echo recognition based on a threshold method, and determining the cloud score of the cloud radar according to different reflectivity factor signal intensities; determining a light rain area and a heavy rain area according to the Doppler velocity; cloud layer boundary information and a hairy rain area are obtained through cloud layer recognition result fusion, and cloud layer recognition and rainfall area recognition are completed; according to the invention, the accuracy of weather prediction is improved.

The invention provides a system abnormity intelligent diagnosis and recovery method and system fusing time sequence logs, and relates to the field of distributed system operation and maintaining.The method comprises the steps that operation logs are collected from a plurality of service nodes of a distributed system, time sequence alignment is conducted, and calling relation and performance measurement data are extracted; time sequence change features are calculated in the sliding time window, dynamic feature vectors are generated through fusion coding, and a cross-service time sequence association graph is constructed; identifying an abnormal service node and matching the abnormal service node with historical fault data to obtain a historical propagation path and a feature vector; calculating a propagation convergence coefficient and a characteristic deviation degree based on a historical propagation path to obtain a causal intensity score; and identifying a fault influence degree according to the score, and adaptively adjusting a resource isolation and flow scheduling strategy. According to the invention, accurate diagnosis and efficient recovery of distributed system faults are realized.

The invention discloses a waistband type falling protection early warning device for old people living alone, and belongs to the technical field of intelligent wearable equipment. The problems that an existing device is single in early warning mode and cannot effectively guarantee the safety of old people living alone are solved, corresponding action results are matched for various data of the old people through the convolutional neural network and the lightweight decision tree model, and if a preliminary judgment result conforms to a normal mode, a judgment result is directly output; if not, triggering a secondary analysis mechanism to further judge whether the old people fall down or not; the GPS positioner is also used for analyzing whether falling behaviors occur at the same position for many times, and if a high-risk position is found, when the old people approach the high-risk position, the warning lamp and the alarm are used for reminding and paying attention to action behaviors; the fall detection accuracy is improved, the possibility of false alarm and missing alarm is reduced, the old people can be actively prevented from falling again in a high-risk area, and a more comprehensive safety guarantee is provided for the old people living alone.

The invention provides an environment supervision method and system based on an edge cloud architecture. The method comprises an edge end device and a cloud platform, wherein the edge end device is arranged on an environment supervision site; the execution steps of the side end device comprise: collecting a pollution source multi-modal data stream; according to the pollution source multi-mode data flow, triggering an alarm through a grading abnormity identification model; in response to the alarm, generating an evidence chain with a timestamp; extracting a monitoring deviation feature D, a behavior anomaly feature B and a semantic feature S according to the evidence chain; compressing the monitoring deviation feature D, the behavior anomaly feature B and the semantic feature S to generate a feature packet Z; and uploading the feature packet Z to a cloud platform. The cloud data matching performance can be effectively improved, and the false alarm rate is reduced.

The invention discloses an urban rail transit energy management method based on multi-source fusion, and the method comprises the steps: employing a support vector machine algorithm to analyze a correlation mode between train intensive operation and passenger flow surge according to an obtained energy demand fluctuation index, and determining a potential energy consumption peak value position; the determined adjustment parameters are obtained, a power supply system control instruction is updated in combination with real-time train track information, and dynamic power supply load configuration is obtained; whether the obtained dynamic power supply load configuration is matched with the current passenger flow surge data or not is judged, if yes, a mode switching signal is sent to an equipment controller, and energy use feedback data after execution is obtained; according to the obtained energy use feedback data, evaluating the response accuracy of the system integration effect to demand fluctuation by adopting a gradient boosting decision tree algorithm, and determining further trajectory optimization suggestions; and updating a train operation scheduling model through the determined trajectory optimization suggestion to obtain an integrated multi-source information linkage mechanism.

The invention relates to the technical field of solid waste incineration automatic control, and discloses a solid waste incineration equipment automatic control method and system.The method comprises the steps that real-time data of solid waste components in a hearth are collected, and an initial multi-dimensional parameter set is obtained through preprocessing; calculating a balance point of the heat value and the water content through fuzzy reasoning; when the balance point exceeds a threshold value, parameter interaction influence is predicted, and a multi-dimensional control vector is generated; performing data fusion and historical data matching in combination with real-time incineration process indexes to obtain an enhanced load distribution adjustment factor; carrying out weight comparison based on the adjustment factor and the balance point, judging a load balance influence index, and carrying out matching correction if the index exceeds a compatible threshold value; updating a load distribution scheme according to a correction result, and generating a final operation strategy; and a control instruction is sent through a feedback cycle mechanism and is continuously optimized, so that closed-loop control is realized. The device can adaptively treat dynamic changes of solid waste components, and the incineration efficiency and stability are improved.

The invention relates to the field of data analysis, in particular to an internet-based convergence media data relation analysis system. The fusion media data relation analysis system based on the Internet comprises a fusion media data acquisition module, a fusion media data processing module and a hot topic analysis module. According to the method, the keywords of the convergence media data are extracted, the corresponding clustering clusters are constructed, then the correlation degree of the two pieces of convergence media data is calculated on the basis of the clustering clusters, and the convergence media data higher than the correlation threshold value are combined to be used for analyzing the hot topic condition of the current time period; and the correlation degree is calculated based on the similarity of the clustering clusters and the TF-IDF value, and the distribution condition of keywords corresponding to the clustering clusters is also considered in the calculation process, so that the accuracy of fusion media data matching can be improved.

The invention provides a multi-source heterogeneous data intelligent matching system applied to a department and wound supply chain online platform, and relates to the technical field of data matching, and the system comprises a data preprocessing module which is used for carrying out the standardization processing of department and wound resource data and generating a data quality score; the cross-modal semantic understanding module is used for receiving a user query, performing unified semantic feature representation on the user query and the medical and invasive resource data, and identifying a user query intention; the intelligent matching engine module is used for performing similarity calculation according to the user query intention and the semantic feature representation thereof and the semantic feature representation of the medical and invasive resource data, generating a matching score in combination with a data quality score, and outputting a matching list; and the feedback optimization module is used for collecting feedback data of the user to the matching list, feeding back the feedback data to the intelligent matching engine module, recalculating the matching score and updating the matching list until a preset stop condition is met. According to the invention, the matching precision and efficiency of the medical and invasive resources can be improved.

The invention provides a two-ticket management and anti-misoperation system and method, the system realizes collaboration through bidirectional interaction of a functional layer and a data layer, a two-ticket generation module obtains user input data from the data layer to automatically generate an operation ticket and / or a work ticket and returns and stores the operation ticket and / or the work ticket, manual filling and paper recording are replaced, and the efficiency is improved. The problems of low ticket generation efficiency and difficult query in the prior art are solved. The anti-misoperation module obtains equipment operation data from the data layer, matches the equipment operation data with an anti-misoperation rule base, outputs anti-misoperation rules, and verifies the equipment operation data in combination with the data layer, so that missing judgment of manual supervision is avoided, and the passive problem of anti-misoperation verification is solved; and the collaboration module performs grading processing according to verification results to realize risk differentiation response. The two-ticket management and anti-misoperation system does not need to depend on a paper flow and manual intervention, tickets are efficiently generated, operation is accurately verified, risks are disposed in a graded mode, and the operation and maintenance efficiency and the safety management and control precision are improved.

The invention relates to the technical field of wind power plant network operation and maintenance, in particular to a method and related equipment for monitoring alarm information, and the method comprises the steps: inputting basic information of a physical machine and a virtual machine, including an equipment model, an IP address, a deployment position and specified field information; a resource binding threshold value is set, and the resource binding threshold value covers the space utilization rate of a CPU, a memory and a disk; monitoring resource use conditions in real time, performing natural language processing on alarm information, and extracting key features; matching the key features with historical data by using a preset classification model, dividing alarm levels and allocating the alarm levels to corresponding processing queues in combination with a resource threshold exceeding degree; and pushing alarm information to the contact person through a multi-mode notification channel according to the alarm level.

Systems and methods include receiving an index of data for exact data matching, wherein the index includes Personally Identifiable Information (PII); receiving policy related to actions to perform for any violations associated with the exact data matching; loading the index and the policy into memory; monitoring traffic for violations, wherein the violations include detection of any values in the index in the traffic; and performing an action responsive to any violations and associated policy. The action can be one of reporting the violation, blocking the traffic associated with the violation, reporting the violation and allowing the traffic associated with the violation when the violation is based on authenticated PII, allowing the traffic associated with the violation when the violation is based on authenticated PII, and a combination thereof.

The invention relates to a method for predicting the service life of a bulb tube of CT equipment and a storage medium. The method comprises the following steps: firstly, obtaining target time sequence data reflecting a degradation state of a target bulb tube of CT equipment; then, screening historical sample data matched with the degradation mode of the target bulb tube from a preset database; and training an initial prediction model based on historical sample data, and taking the trained initial prediction model as a target prediction model matched with the target bulb tube. And finally, inputting the target time sequence data into a target prediction model, and predicting the remaining service life of the target bulb tube through a recursive multi-step prediction mechanism. By screening the historical sample data matched with the target bulb tube degradation mode, misjudgment on a personalized fault mode can be reduced, and meanwhile, through a dynamic model training mechanism, a target prediction model can be matched for each target bulb tube, so that the precision of predicting the service life of the bulb tubes of the CT equipment can be improved.

The embodiment of the invention provides an address data matching method and related equipment, and belongs to the technical field of geographic information services. The method comprises the following steps: constructing an address annotation corpus according to input address information data and a preset address database; the method comprises the following steps: generating a geographic information embedding vector according to a preset geographic information knowledge graph, performing address element analysis in combination with an address annotation corpus to obtain an address element sequence so as to construct a dictionary tree, and performing similarity screening through a spatial hierarchical matching algorithm to obtain a similar address set; generating an address embedding vector matrix through a preset word embedding vector model, and performing feature extraction through a preset semantic feature extraction model to obtain semantic-level similar features; according to input address information data, multi-dimensional character similarity matching is carried out to obtain character-level similar features, then weighted fusion is carried out in combination with semantic-level similar features, and target matching address data is determined according to a weighted fusion result. According to the embodiment of the invention, the address data matching accuracy and efficiency can be improved.

The invention discloses an AIS information and video data fusion method. The method comprises the following steps: collecting and preprocessing AIS and video data; constructing a constant acceleration model to interpolate the AIS data, and projecting AIS latitude and longitude coordinates to a video pixel coordinate system to obtain a target trajectory; detecting a video ship by using a YOLOX model, and tracking through a MotionTrack algorithm to obtain a video trajectory; ship motion features of the tracks in the AIS and the video data are extracted respectively; constructing a comprehensive measurement function fusing the Euclidean distance, the course and the navigational speed similarity; performing data matching by adopting a Hungary algorithm to obtain a matching result of the AIS and the track in the video data; verifying a matching result through abnormal value elimination and category consistency verification; and according to a matching result, fusing and displaying the matched AIS information and the video image. The AIS information and the visual target information are comprehensively utilized, and the information matching result is determined by using multiple clues, so that the fusion accuracy is improved, and the precision and reliability of multi-source information fusion in maritime affair monitoring are improved.

Disclosed in the present application are a display device, and a mode switching method for the display device. The display device may comprise at least one processor, which is connected to a display, a communication apparatus and a memory, and may be configured to execute a computer program stored in the memory, so as to cause the display device to execute the following operations: when a mode switching application detects that a first screen mirroring device is connected, controlling the mode switching application to create a first window, and displaying, in the first window, screen mirroring data sent by the first screen mirroring device, wherein the mode switching application is started after the display device is powered on; and in response to a mode switching operation, controlling the mode switching application to perform switching to a target mode indicated by a mode switching instruction, and according to first layout data matching the target mode, displaying content to be presented, wherein said content comprises the screen mirroring data sent by the first screen projection device, the first layout data is used for indicating display parameters of each piece of said content, and at least comprises a display size and a display position after the first window is reset. Therefore, the mode switching efficiency is improved.

The invention discloses a gene sequencing sample data matching method based on a micro-fluidic chip, relates to the technical field of gene sequencing sample matching, and aims to solve the problem that the matching rate is reduced due to inaccurate analysis of gene sequencing samples. According to the method, multi-strategy comparison and candidate set screening are adopted, multi-dimensional comparison of sequences, variation and functions is combined, the accuracy is improved, the adaptability to complex samples is enhanced through quantitative index and biological verification evaluation and dynamic optimization of comparison strategies, the matching reliability and practical value are remarkably improved, the clinical and scientific research diversified requirements are met, and the method is worthy of popularization and application. Sample types such as blood and cells are adapted through a differential lysis strategy, impurities such as proteins and salts are removed through stepped purification, and the nucleic acid concentration and the fragment state are unified in combination with standardized treatment, so that interference is reduced from the source.

The invention provides a medical physical examination data intelligent processing and large model offline deployment method and system. The method comprises the following steps: performing online configuration in an offline deployment basic environment, deploying a physical examination data processing algorithm module, downloading a pre-training large model file and a reasoning framework from a model warehouse, and generating a distributable mirror image through a packaging command; performing offline deployment on the distributable mirror image, transmitting the mirror image to a server without an external network through a physical medium, importing and loading the mirror image, and starting a container service; cleaning and standardizing the received physical examination data, matching the standardized data with a medical data matching library, and calculating the severity level; and preprocessing the unstructured medical text, calling an off-line deployed large model to perform semantic analysis and generate an explanatory suggestion, and integrating processing results to generate a standardized physical examination report. According to the invention, off-line deployment and application of a large model in an external network-free environment are realized, and the intelligent level and efficiency of physical examination data processing are improved.

The invention relates to the technical field of medical data processing, and discloses a disease risk assessment method based on a disease risk knowledge graph, the disease risk knowledge graph comprises a disease risk rule and a disease knowledge entity, and the disease knowledge entity comprises a focus position entity; performing organ positioning according to the physical examination data of the target object, and determining a target organ; performing organ matching and index data matching in a disease risk rule based on the target organ and the physical examination data to obtain a risk matching rule corresponding to the target organ; performing disease risk level analysis on the target organ according to the risk matching rule to obtain a disease risk level of the target object about the target organ; generating a physical examination report of the target object according to the physical examination data, the disease risk level and the target focus position; wherein the physical examination report comprises a three-dimensional model used for displaying the target focus position. The method has the beneficial effects that the pertinence and efficiency of disease risk assessment are improved, and the target object is helped to understand the health state of the target object.