951 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 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.

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 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 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 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 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.

Methods, systems, and computer-readable storage media for receiving use case data descriptive of a use case that includes tabular data matching, the use case data including process data, task data, table schema data, and a set of few-shot examples, populating a CoT extraction prompt template using the use case data to provide a CoT extraction prompt, prompting a LLM using the CoT extraction prompt, receiving, from the LLM, a CoT script responsive to the CoT extraction prompt, generating an inference prompt template using the CoT script, and deploying the inference prompt template for production inference.

The embodiment of the invention discloses a network asset inspection method, device and equipment and a storage medium, and relates to the field of network security. The method comprises the steps of searching first network asset data matched with a keyword on a network in response to the keyword which is input by an asset surveying and mapping tool and is related to a target object; the first network asset data is compared with historical network asset data of the target object, second network asset data are screened out, and the second network asset data comprise unknown network asset data and / or changed network asset data; and outputting at least partial data of the second network asset data. All network assets are searched through the asset surveying and mapping tool, and are compared with historical network asset data, so that unknown network asset data and changed network asset data are accurately screened and timely output, and the efficiency of network asset inspection is improved.

The invention discloses a three-dimensional geologic modeling method based on deep learning, which belongs to the technical field of geologic model modeling, and comprises the following steps: acquiring multi-source geologic data and carrying out fusion processing, generating a preliminary three-dimensional geologic attribute model through multi-scale feature extraction, synchronously generating a theoretical three-dimensional geologic model through physical simulation and carrying out comparison, generating three-dimensional difference volume data, performing weight distribution on the three-dimensional difference volume data and quality indexes of multi-source geological data extracted from the three-dimensional grid data, generating dynamic weight distribution, and performing weighted fusion on the preliminary three-dimensional geological attribute model and the theoretical three-dimensional geological model to generate an optimized three-dimensional geological model; and based on the three-dimensional difference volume data, performing iterative optimization by utilizing the optimized three-dimensional geologic model to obtain a final three-dimensional geologic model. Through data driving and physical simulation parallel modeling, dynamic weighted fusion and iterative feedback optimization, a final three-dimensional geologic model with high data matching degree and geologic rationality can be generated.

The invention relates to the technical field of campus resource management, and discloses a campus resource collaborative management method and system based on big data. The method comprises the following steps: acquiring basic use information of campus resources, and generating a preliminary resource allocation strategy in combination with resource attribute details; monitoring resource real-time state information, evaluating whether a preliminary strategy needs to be modified or not, collecting detailed resource use records of each monitoring partition after the modification is confirmed, obtaining resource distribution characteristic information through characteristic analysis, and further calculating a resource distribution characteristic index of each monitoring partition; matching the indexes with the previous records one by one, correcting the preliminary strategy according to a matching conclusion to obtain an optimization strategy, if the indexes are not completely consistent with the previous records, calculating the approximation degree of the indexes and the previous records, and correcting the preliminary strategy according to the approximation degree. Resource information is integrated through a big data technology, real-time monitoring and historical data matching are performed, dynamic optimization of resource allocation is realized, the management requirements of various resources in a campus are adapted, and the accuracy and adaptability of resource collaborative management are improved.

The invention discloses a fault recognition method and system, computing equipment and a readable storage medium, and the method comprises the steps: responding to abnormal sound of a target vehicle, and collecting an audio signal and a driving condition parameter of the target vehicle in real time; converting the audio signal from a time domain to a frequency domain, and extracting a feature vector of the converted audio signal; and matching at least one of the audio signal, the feature vector and the driving condition parameter with corresponding data in a preset feature library to output a fault recognition result. Thus, by collecting the vehicle audio and driving condition data in real time and combining the frequency domain feature vector with the multi-dimensional data matching of the preset feature library, high-precision and self-adaptive vehicle abnormal sound fault automatic diagnosis is realized, the detection efficiency and accuracy are remarkably improved, and the manual dependence is reduced.

The invention discloses a new energy truck carbon emission monitoring, verification and correction method and system, belongs to the technical field of new energy automobile carbon management, and aims to solve the problems that the dimension of existing new energy truck carbon emission monitoring data is incomplete, the accounting deviation is large, charging carbon emission attribution is distorted, and full-process dynamic management and control are lacked. The method comprises the steps that in the loading stage, basic information of vehicle-mounted goods and new energy trucks is obtained, a loading initial vector and a parameter incidence matrix are generated, alternative paths are split into carrying sub-paths, a feature table is constructed, and an initial carbon emission reference value is generated in combination with historical data matching; in the carrying stage, parameters and actual carbon emission are corrected based on real-time data, carbon emission values of alternative paths are updated, and recommended paths are screened; when the charging pile is connected, the charging carbon emission is accurately calculated and is split and corrected according to the transportation progress; and finally identifying an abnormal path, generating a standardized report and updating a historical database. According to the invention, accurate monitoring and dynamic correction of the whole process are realized, and reliable data support is provided for low-carbon transportation management and control.

The invention provides a method, a system, equipment and a medium for analyzing running states of multiple automatic warp tying machines, and belongs to the technical field of automatic warp tying machines. Equipment health, warp tying efficiency, warp process, joint quality, fault early warning and associated loom data are acquired from multiple pieces of equipment in real time; a standard data set is formed through intelligent routing transmission, data cleaning, format conversion and aggregation processing; and adopting a self-adaptive strategy to match an optimal analysis model for various types of data for analysis processing, comparing a result with a multi-machine cooperative operation reference value, marking abnormity, and summarizing state results according to device numbers. Multi-device data full-link closed-loop management is realized, and the monitoring efficiency and accuracy are improved; through cross-device data association verification and multi-dimensional feature fusion, the fault positioning and prediction capability is enhanced; operation state results are fed back to an equipment end in real time, stable operation of equipment is effectively guaranteed, fault risks are reduced, and production efficiency and warp tying quality are improved.

The embodiment of the invention discloses a business receipt and invoice data matching method and system, and the method comprises the following steps: accessing original business receipt data and invoice data from a plurality of heterogeneous data sources through a uniform interface, and carrying out the data cleaning according to preset mapping, merging, splitting and conversion rules, generating a standardized matching flow order; adopting streaming data loading and a Worker parallel computing mechanism to carry out multi-dimensional matching on business receipt and invoice data in the standardized flow bill, and generating a relation matrix representing a corresponding relation between the receipt and the invoice based on a matching result; and automatically checking the relation matrix by calling a rule engine and a machine learning model, marking the matching result of the business document and the invoice which are checked to be abnormal, pushing the matching result to manual auditing, and feeding back the manual auditing result to a knowledge base to optimize the subsequent matching and checking rule. According to the embodiment of the invention, the matching efficiency of the business document and the invoice data and the accuracy of the matching result can be improved.

The invention discloses a college canteen food waste monitoring and incentive system and method based on dynamic feedback, relates to the technical field of intelligent catering management, and realizes accurate recognition and behavior guidance of food waste behaviors through datamation monitoring and dynamic feedback of the whole catering process of a college canteen. The system automatically collects the types and initial weights of dishes in a meal ordering link, intelligently recognizes the types, areas and humidity states of dinner plate residues in a recycling link, and further achieves the precise calculation of the individual waste amount. Through data matching and behavior clustering analysis of a server side, individualized waste archives and group comparison statistics can be generated, and closed-loop management from waste discovery to feedback excitation is realized.

The invention relates to a production line vehicle type configuration transmission and verification method, and the method comprises the steps: obtaining vehicle type configuration data corresponding to a work-in-process when an intelligent transportation trolley enters an initial station of a production line; the vehicle model configuration data are written into the flexible conveying bracket provided with the work-in-process product; the intelligent transportation trolley is controlled to carry the flexible conveying bracket to enter a plurality of target stations matched with the vehicle type configuration data; when the intelligent transportation trolley arrives at any target station, vehicle type configuration data are read from the flexible transportation bracket; verifying the configuration state of the current station based on the vehicle type configuration data; if verification is not passed, the target station is controlled to execute configuration switching operation, and verification is executed again after configuration switching is completed; and if the verification is passed, controlling the target station to execute the corresponding production operation. By adopting the method and the device, the consistency of the vehicle type configuration data acquired by the station and the actual vehicle type configuration data of the product in process can be improved, and the processing abnormity caused by wrong station configuration is reduced.

The invention relates to the crossing field of artificial intelligence and big data, and discloses a data matching method based on an AI model and knowledge graph driving, which comprises the following steps: intelligently capturing policy data, collecting enterprise data, and carrying out document processing and structured storage; constructing a policy knowledge graph and realizing enterprise data enhancement, including knowledge base initialization and AI auxiliary modeling; a mixed matching engine and a rule reasoning mechanism are integrated, dynamic and accurate matching of enterprises and policies is achieved, a causal discovery algorithm module is embedded in the mixed matching engine and used for recognizing the causal relationship between policy terms and enterprise behaviors, mismatching caused by false correlation is avoided, and the purposes of improving the intelligent level of policy matching and improving the policy matching efficiency are achieved. Personalized and high-precision policy recommendation support is provided for enterprises, meanwhile, scientificity and effectiveness of government resource allocation are improved, and good practical value and popularization prospects are achieved.

The invention relates to the field of hydrological forecasting, and discloses a distributed hydrological model construction method, system and equipment based on feature units, and the method comprises the steps: building a session flood historical data set according to the collected topographic data, soil data, hydrological data and meteorological data, dividing the topographic data in the session flood historical data set into feature units, the other soil data, hydrological data and meteorological data are matched to each feature unit, and a spatial topological relation is constructed based on the feature units; constructing a distributed hydrological model based on the spatial topological relation to calibrate runoff production model parameters, and calibrating confluence model parameters according to a runoff production model parameter calibration result; and according to a parameter calibration result, various monitoring and forecasting information and different levels of flood early warning release standards, manufacturing and releasing flood early warning information. According to the method, the distributed hydrological model is constructed based on the feature units, and real-time flood operation forecasting can be carried out.

The embodiment of the invention provides a multi-modal data set construction and dynamic updating method and device based on a large model, and effective expression of data is realized through innovative design of a semantic alignment system and multi-modal analysis and feature fusion. And constructing a vectorization mechanism, and establishing a reliable data screening model in combination with feature indexes and similarity matching. Incremental updating is introduced, and the timeliness of a data set is ensured through matching degree evaluation and dynamic optimization. According to the method, the defects of the traditional technology in the aspects of feature alignment, data matching, dynamic updating and the like are effectively overcome, and technical guarantee is provided for data management.

The invention relates to the technical field of data processing, and particularly provides a dynamic updating method, system and device for an AI intelligent question and answer knowledge base and a medium, and the method comprises the steps: obtaining to-be-updated content, extracting effective information from the to-be-updated content through a semantic recognition technology, and storing the effective information in a temporary file; matching the temporary file with metadata of a file which is uploaded to a knowledge base in a pre-constructed metadatabase; if the metadata matched with the temporary file exists, not executing the operation of updating the temporary file to the knowledge base; if the metadata matched with the temporary file does not exist, calling an interface of a knowledge base platform to update the temporary file to a knowledge base; and obtaining metadata of the temporary file returned by the knowledge base platform in the knowledge base, and storing the metadata in the metadatabase. Effective information is extracted through semantic recognition, and a metadata matching mechanism is combined, so that intelligent dynamic updating of the knowledge base is realized.

Systems and methods for intelligent Human Interface Devices (HIDs). In some embodiments, an HID may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the HID to: receive data from a sensor coupled to the processor; and transmit an indication of an input received by the processor to an Information Handling System (IHS) coupled to the HID in response to a determination, by the processor, that the data matches a biometric profile.

Provided in the present application are a cache updating method and apparatus based on a multi-level cache, and a device and a medium. The method comprises: if target cache data matching target service data is found in a first-level cache, determining a first cache existence duration of the target cache data on the basis of a cache duration determination sub-policy in an asynchronous cache update policy; if the first cache existence duration meets a valid cache determination sub-policy in the asynchronous cache update policy, generating an asynchronous refresh task, and submitting the asynchronous refresh task to a second-level cache by means of a first task deduplicator, wherein the asynchronous refresh task is used for instructing that the second-level cache be searched for cache update data used for updating the target cache data; and receiving the cache update data returned by the second-level cache by means of the first task deduplicator, and updating in the first-level cache the target cache data to the cache update data. By using the present application, the timeliness and reliability of cache updating can be improved.

The invention provides a medical data sharing interface based on a standardized API and a low-code construction method. The method comprises the steps that a set of standardized medical core data models is predefined; a unified data sharing service API layer is constructed, an adapter used for being in butt joint with a heterogeneous medical data source and converting the heterogeneous medical data source into data matched with a predefined model format is configured, and an API interface is generated based on the predefined model; a component library is preset through a visual interface configuration platform, each component in the component library is bound with a field of a predefined model, the components are arranged and / or combined in a dragging mode, and a data binding relation between the components and an API interface is configured; and analyzing and generating a structured interface description file according to the information of visual interface construction and configuration, dynamically loading the interface description file through an engine when a client runs, calling an API (Application Program Interface), and rendering a final user interface. According to the scheme, the development cycle can be shortened, the ability threshold of developers can be reduced, and good expandability is achieved.

The invention relates to the technical field of multi-mode perception, and discloses a multi-mode perception fused edge intelligent control method and system, and the method comprises the steps: carrying out the frequency calibration of RGB-D camera data, laser radar data and ultrasonic sensor data, and obtaining a first sensor data set; performing timestamp synchronization based on the first sensor data set to obtain a second sensor data set; carrying out adaptive time window adjustment and synchronous optimization on the second sensor data set according to a detection result of the movement speed of the old person to obtain a third sensor data set; and navigation path calculation is performed based on the third sensor data set, and a navigation control instruction of the intelligent old-age care robot is output, so that the heterogeneous frequency data matching precision is improved, and a personalized navigation decision is realized.

The invention relates to the technical field of supply and demand data matching, and discloses a supply and demand data dynamic optimization system and method based on a full life cycle, and the system comprises a decision module, a data analysis module, a supply module and a storage and transportation module. Analyzing the supply portal information and the appeal portal information in real time to obtain layout analysis data appeal information; evaluating and sorting the layout analysis data according to the appeal information to obtain a plurality of supply sorting tables; constructing an initial supply and demand plan according to the supply sorting table and the demand information, and inputting the initial supply and demand plan into a supply portal for rationality analysis to obtain dynamic adjustment data; the initial supply and demand plan is updated according to the dynamic adjustment data, the supply portal constructs a production list according to the target supply and demand plan, and the appeal portal generates storage data and a transportation plan according to the production list. According to the method, all data of the supply and demand parties are matched and optimized by constructing a full-period supply and demand management architecture, so that the supply and demand matching efficiency is improved.

The invention relates to a vehicle control method and device, a vehicle, a computer readable storage medium and a computer program product. The method comprises the steps that in the vehicle driving process, driving data of a vehicle and driving scene information pre-configured for the vehicle are acquired; determining a target driving scene matched with the driving data from the driving scene information; determining a torque control strategy of the vehicle according to the target driving scene; under the condition that the vehicle is controlled to run according to the torque control strategy, if the vehicle meets the torque adjusting condition, the current torque of the vehicle is adjusted. By adopting the method, the accuracy of vehicle control can be improved.

The invention discloses a server hardware link diagnosis method and a server hardware link diagnosis system, relates to the technical field of computer system fault diagnosis, and discloses the server hardware link diagnosis method and the server hardware link diagnosis system. Through the steps of obtaining a diagnosis rule configuration file, collecting software and hardware state data, carrying out matching analysis to generate a diagnosis path, executing diagnosis processing, carrying out correlation analysis, generating a fault report and the like, the problems of software and hardware diagnosis splitting and path stiffness in the prior art are solved, and collaborative diagnosis and dynamic path generation of software and hardware faults are realized. And the fault positioning accuracy and the system recovery timeliness are improved.

The present disclosure provides an apparatus for restoring the quality of magnetic resonance images based on a deep learning model and a method of controlling the same. The method includes: obtaining a training image corresponding to each magnetic resonance image by applying at least one of a plurality of elements set in connection with the quality of the magnetic resonance image to a magnetic resonance signal corresponding to the magnetic resonance image; obtaining a training dataset including the magnetic resonance image as label data and the obtained training image as input data matching the label data; and training a neural network model based on the training dataset and context data corresponding to the training image. Obtaining the training image includes distorting the magnetic resonance signal by applying the at least one of the plurality of elements and obtaining the training image based on the distorted magnetic resonance signal.