497 results about "Data combination" patented technology

Provided are system, method, and device for automatically enhancing future prediction using a reservoir transformer in a machine learning model. According to example embodiments, the system may include: a memory storage storing computer-executable instructions; and at least one processor communicatively coupled to the memory storage, wherein the at least one processor may be configured to execute the instructions to: obtain current input data representing a current state of a complex system; determine a plurality of readout data based on previous input data representing a previous state of the complex system using a plurality of reservoirs; combine the plurality of readout data to form an ensemble reservoir data; and determine predicted output data representing a predicted state of the complex system based on the ensemble reservoir data and the current input data using a transformer.

The invention provides a multi-mode PDF (Portable Document Format) document analysis method, device and equipment and a medium, and the method comprises the following steps: loading a PDF document and carrying out preprocessing, including page splitting and content cleaning, to generate standardized document data; dynamically extracting contents in the standardized document data, wherein the contents comprise paragraphs, pictures and table elements; processing the dynamically extracted pictures, including shielding meaningless pictures based on a preset rule, and analyzing picture contents by using a multi-modal model to generate readable picture information; processing the dynamically extracted table, including optimizing and merging the table structure into a single element format to generate structured table data; combining paragraphs, readable picture information and structured table data, converting the paragraphs, the readable picture information and the structured table data into a complete structured document format, and inserting in key positions to enhance coherence context description; and outputting the complete structured document format as a final analysis result. According to the method, the analysis precision and the knowledge extraction efficiency of the complex PDF document can be remarkably improved.

The invention relates to the technical field of flight management, in particular to a flight departure guarantee resource allocation scheduling optimization management method, which comprises the following steps: according to a runway, a running sequence and a time interval corresponding to a flight shift list, constructing a flight state diagram for the flight shift list in a preorder and postorder manner; determining the transfer cost of each state in the flight state transfer process by taking the maximum capacity and the minimum adjustment time interval of each node in the flight state diagram in a unit time period as constraint conditions, and sequencing the flights into a time-adjusted flight list according to the transfer cost; performing iterative solution by using the timing flight list, determining an optimal adjustment time interval in unit time, and determining an adjustment quantity in a unit time period according to the adjustment time interval in combination with time slot allocation; when the adjustment quantity accords with a preset constraint rule, performing data combination on the corresponding flights, and regarding the combined data as an output adjustment scheme; the efficiency and the performability of flight scheduling processing are realized.

The invention provides a component-level collaborative editing control method, which is applied to a multi-user collaborative editing control system, and the system comprises a plurality of front-end engines and a back-end server. A front-end engine obtains user editing operation data and a rear-end real-time version snapshot, component structure difference comparison is carried out, and a component operation list is generated; and performing component conflict judgment based on the operation list, merging and editing operation data according to a conflict judgment result and a preset conflict resolution strategy, generating processed version snapshots, sending the processed version snapshots to a rear end, storing the processed version snapshots by a rear-end server, and sending the processed version snapshots to each front-end engine. Compared with the prior art, the method has the advantages that the data transmission quantity and the load of the rear-end server are reduced by a lightweight architecture through the front-end component level difference comparison and the preset conflict resolution strategy, the rear-end server does not need to be frequently requested for conflict resolution and data merging, the response speed and the collaborative editing efficiency are remarkably improved, and the user experience is improved. And better user experience is brought to the user. The system has the same beneficial effects.

The invention relates to a PLC-bridging gateway internet-of-things automatic identification method, system and device and a medium. The method comprises the following steps: sequentially sending handshake detection signals to a plurality of PLC devices and receiving response messages; forming a candidate handshake data combination set, and completing handshake matching through a priority algorithm and an adaptive polling mechanism; verifying the response frame, analyzing the equipment information, and confirming the active state and communication parameters of the PLC equipment; generating a drive binding strategy according to a matching result, and distributing a session identifier for the drive binding strategy; generating a session identifier of the target PLC equipment, and updating a session routing table in the bridging gateway; and translating the industrial data collected by the target PLC device into an Internet of Things protocol data packet and uploading the Internet of Things protocol data packet to a cloud data center. According to the invention, automatic identification and rapid adaptation of various interfaces and protocols can be realized; the communication stability and real-time performance are improved through dynamic scheduling and route updating; uniform data uploading is supported, and efficient deployment of cloud analysis and the industrial Internet of Things is facilitated.

The invention discloses a multi-stage wind power abnormal data combination cleaning method, and belongs to the field of new energy power generation data processing. Aiming at the problems of various types of abnormal values of wind power original data, serious interference and low cleaning precision, and single anomaly detection means, easy missing detection and misjudgment and the like in the prior art, the invention provides a staged combined cleaning strategy, which comprises the following steps of: firstly, dividing equal interval sections of wind speed and power, and eliminating isolated point type anomalies in distribution by using double quartile analysis; a CFSFDP density peak value clustering algorithm is introduced, low-density anomaly clusters are mined according to a density-distance joint criterion, and the recognition capability of structural aggregation anomaly is improved through two rounds of clustering; performing segmentation modeling on a wind speed-power relation by using upper and lower envelope line fitting based on a function, and removing envelope outer drift type noise; and finally, complementing edge missing data by using an interpolation algorithm. According to the method, the systematicness, precision and adaptability of the wind power data cleaning process are remarkably enhanced, high-quality data are provided for subsequent power prediction and energy optimization scheduling, and the application prospect is wide.

The invention relates to the technical field of model testing, in particular to a model testing method and device and electronic equipment, and is used for solving the problems of long test data combination time consumption and low coverage rate of a model testing mode in the related technology. The multiple features are classified, a core feature set, a common feature set and an edge feature set are obtained, and the model can be a deep learning model; generating a test set of the model according to a differentiated data generation strategy of feature importance on the basis of the rule set of the service type adapted to the model, the core feature set, the common feature set and the edge feature set, and performing model performance test on the model by using the test set to obtain a test report; therefore, the efficiency of model algorithm testing is improved.

The application discloses a power equipment defect detection method, system and device based on multi-modal alignment, and particularly relates to the technical field of power equipment detection, and the technical points are as follows: the method comprises the following steps: in the collected visible light image, infrared image and ultrasonic signal, the spatial feature difference and the time feature difference between every two modal data are obtained; the spatial feature difference and the time feature difference are subjected to logic regression processing, the alignable coefficient between every two modal data is obtained, the to-be-aligned data combination for power equipment defect detection is determined based on the alignable coefficient; the to-be-aligned data combination is subjected to data alignment, the aligned modal data is obtained, and according to the aligned modal data, the time sequence model is used for defect detection analysis on the power equipment, so that the power equipment defect detection result is obtained.

The invention provides an electric power monitoring data general transmission method and system based on a Beidou short message, and relates to the technical field of electric power monitoring systems. The method includes; a substation collects power monitoring data of a power system, classifies and evaluates the power monitoring data, allocates priorities, and generates classified monitoring data with priority marks; the substation determines a data item value corresponding to the power monitoring data based on the priority mark, screens out a corresponding data combination when the transmission benefit is maximized, and encapsulates the data combination into a transmission frame with an LPDU frame structure, and the transmission benefit is formed by superposing the data item values corresponding to the power monitoring data contained in the data combination; the substation sends the transmission frame to the master station by using a self-adaptive transmission strategy model; and the master station performs intention analysis and intention verification on the transmitted power monitoring data, generates a control instruction and issues the control instruction to the substation. According to the invention, the problem of efficient data coding under the limited frame length is solved.

A system and a method for automatically assisting physicians during patient encounters includes transcribing and diarizing physician-patient interactions, extracting clinical concepts, and combining data with patient history data to provide suggestions to the physicians. A speech and gesture recognition module captures audio from patient-doctor interactions and transcribes the audio into text in real-time. A natural language processing module diarizes the transcribed text to attribute speech. A clinical concept extraction module identifies and extracts clinical concepts from transcription. A clinical recommendation module integrates real-time data with historical patient records and analyzes the combined data set to generate evidence-based suggestions to the physician. A physician's own historical data is validated to generate a unique profile for each physician. Interactions with the physician are analyzed to understand decision-making patterns. The physician's profile is updated and future physician decisions are forecast based on past behavior.

The invention provides an azimuth transverse wave remote detection data processing method, system and device and a medium. The method comprises the steps that an instrument is adopted to collect novel four-component transverse wave data (xx, xy, yx and yy) of a target well section; under a coordinate system (x, y) of the instrument, synthesizing an XX reflected wave signal with an angle defined relative to the x-axis direction of the instrument by using the orthogonal dipole four-component reflected signal, and defining the XX reflected wave signal as an angle when the reflected wave signal reaches the maximum amplitude; obtaining two cross component signals xy and yx by using novel four-component shear wave data (xx, xy, yx and yy), performing sliding windowing on the cross component signals xy and yx, performing Fourier transform on the signals in the window to obtain phase spectrums, and comparing the phase spectrums of the two cross component signals to obtain an actual phase difference; according to a novel four-component data combination mode, changing the orientation of the reflector, theoretically calculating the theoretical phase difference between the two cross component signals xy and yx, and establishing a rule chart of the cross component signals along with the orientation change of the reflector outside the well based on the theoretical phase difference; and judging the real azimuth angle of the reflector according to the rule plate.

The invention discloses a USB key identity authentication method, system and device based on a digital signature trusted chain and a medium, and belongs to the technical field of information security, and the method comprises the following steps: after a receiving terminal accesses a USB key, reading a digital certificate, collecting a device identifier, a network parameter and geographical location information, generating first environment abstract data through abstract processing, and signing; and the authentication server stores the abstract data after passing the signature verification. In the authentication request stage, the server generates random challenge data; the receiving terminal collects the current environment information to generate second environment abstract data, and the second environment abstract data is signed and sent again after being combined with the challenge data. And the server extracts the second abstract data after signature verification, performs similarity comparison with the first abstract data, and confirms that the identity authentication is valid when conditions are met. According to the method, the binding of the environment characteristics and the identity is realized, the protection capability of the U-type shield authentication system on counterfeiting, cloning and replay attacks is remarkably improved, and the credibility and the stability of an authentication result are enhanced.

A method for forming a prompt for use with a large language model includes receiving an input query, generating query augmentation data relevant to the query, wherein the query augmentation data includes one or more examples of queries and respective responses, wherein the query augmentation data is selected based on the input query, wherein the selecting of the query augmentation data is further based on characteristics of the large language model, and forming the prompt by combining the input query with the query augmentation data.

The invention discloses a federal category forgetting method based on label reconstruction and collaborative compression. The federal category forgetting method comprises the implementation steps that a client performs gradient matching optimization on samples randomly sampled from original data to obtain compressed data; after a forgetting request is received, reconstructing a local data label needing to be forgotten, and combining the data label with non-forgetting compressed data to form a forgetting training set; freezing the original model, finely adjusting an additional low-rank matrix by using a forgotten data set, regularizing by applying an F2 norm, and uploading the trained low-rank matrix to a server; and the server aggregates the low-rank matrix uploaded by the client and performs sparse processing, and then sends the low-rank matrix back to the client for training. According to the method, forgetting of forgotten category data is realized while remaining category performance of the model is kept, and calculation and communication overhead in a federal category forgetting process is greatly reduced.

The invention discloses a vertical superfinishing machine intelligent servo control method based on dynamic parameter identification, and relates to the technical field of servo control. Comprising the steps that first sensing equipment is arranged on a key motion axis of target equipment and used for obtaining vibration data of the motion axis, and vibration information items are obtained; and second sensing equipment is arranged on the oilstone unit, is pressure and temperature integrated sensing equipment and is used for acquiring real-time pressure data and temperature data of the oilstone to obtain a pressure information item and a temperature information item. According to the method, damage sorting is combined, low-damage combinations with different oscillation frequencies and feeding speeds are preferentially selected to serve as equipment execution, updating information of vibration information items, pressure information items and temperature information items is deeply obtained, secondary adjustment is conducted on initial information items, and the accuracy of the equipment is improved. Therefore, oilstone driving control based on dynamic parameter identification of vibration data, temperature data and pressure data combination is realized.

A computer-implemented method of performing robotic simulation and design may include performing a simulation where a robot interacts with a user, and generating sensor data indicative of the robot interaction with the user during the simulation. The computer-implemented method may include generating discussion data indicative of user feedback from the simulation, generating form data associated with the user feedback from the simulation, and combining the sensor data, the discussion data, and the form data in a multimodal signal. The computer-implemented method may include determining a design characteristic of the robot based on the multimodal signal, and augmenting a robot model to incorporate the design characteristic using a machine learning algorithm.

The invention discloses a five-axis numerical control machine tool machining control method and system based on visual inspection, and relates to the technical field of visual inspection methods. Multiple pieces of surface data of the machining surface of a workpiece are determined based on detection of a follow-up machining image at the current moment; the dynamic machining grade of the five-axis numerical control machine tool is determined according to the multiple pieces of surface data, the current machining data combination of the five-axis numerical control machine tool and the machining requirement of the workpiece, and the accuracy of the dynamic machining grade of the five-axis numerical control machine tool is improved; optimizing the current processing data combination of the five-axis numerical control machine tool based on the surface state gradient map, the dynamic processing grade of the five-axis numerical control machine tool and the corresponding processing efficiency; determining a dynamic repair event of the five-axis numerical control machine tool according to the machined surface of the workpiece, the surface repair tool of the five-axis numerical control machine tool and the current state of the five-axis numerical control machine tool, and determining a repair-machining synchronous control system according to the dynamic repair event of the five-axis numerical control machine tool, the current machining event and the dynamic stability coefficient of the workpiece.

A computing system is configured to (i) receive input data for a visual interface design, the input data including a target accessibility compliance standard and initial design data for at least two visual interface design elements, (ii) based on the input data, determine a respective set of operations to apply to generate accessibility-compliant design data for each of the visual interface design elements, (iii) apply each respective set of operations to the respective initial design data and thereby generate the accessibility-compliant design data for each of the visual interface design elements, (iv) combine the accessibility-compliant design data for each of the visual interface design elements to thereby generate composite accessibility-compliant design data for a composite visual interface design element, and (v) based on the accessibility-compliant design data for the composite visual interface design element, cause a visual representation of accessibility-compliant content for the composite visual interface design element to be displayed.

Systems for fusing arthroscopic video data are described. A system comprises an arthroscopic assembly, an inertial measurement unit (IMU) mounted on the arthroscopic assembly, a processor, and a processor-readable storage medium. An arthroscopic surgical plan, images from the arthroscopic assembly, and measurements from the IMU may be obtained. The images and the measurements may be combined to form a data combination. The data combination may be filtered to form a fused data set. The fused data set may control a device. A map of an arthroscopic surgical site may be created based on the fused data set, and a position of the arthroscopic assembly with respect to the arthroscopic surgical site may be calculated. The arthroscopic surgical plan may be updated based on at least one of the map of the arthroscopic surgical site and the position of the arthroscopic assembly.

The invention discloses an intelligent control method and system for a train based on a slip scene, and relates to the technical field of intelligent control, and the method comprises the steps: determining a corresponding slip compensation distance based on the event content of a slip control event, a slip data combination of wheels and corresponding speed data; and according to the slip compensation distance, the corresponding slip position deviation amount and the corresponding slip virtual distance, an intelligent control system of the train in the slip scene is determined, and the accuracy of the intelligent control system of the train in the slip scene is improved. Determining a plurality of slip positions based on the intelligent control system, the slip state of the train and the movement event of the wheels, and determining a signal loss event of the train according to the plurality of slip positions and the movement path of the train; the protection area of the train is determined according to the signal loss event and the trackside subsystem, the running mode of the train is determined based on the protection area of the train, the current speed of the train and the corresponding working state, and the accuracy of the running mode of the train is improved.

The invention discloses a data management method, system and device for a semiconductor manufacturing execution system and a medium, and the method comprises the steps: creating or obtaining a unique identifier for connecting an upper layer component and a lower layer component in a component tree, and enabling each layer component of the component tree to achieve the isolation of component states at a hierarchical boundary through mapping state data corresponding to different action ranges; confirming a mixing mode of context data between the upper-layer component and the lower-layer component; mixing the state data of the upper-layer component and the context data of the lower-layer component based on the mixing mode and the unique identifier to form current action domain data corresponding to the lower-layer component; and the lower-layer component obtains the business data provided for the upper-layer component through the action domain component based on the unique identifier in the current action domain data, so that the business data can be used by the business. According to the method, a dynamic state isolation mechanism is realized, a state management tool can well realize component-level state isolation, and extraction and reuse of complex services are realized; and the data combination form among the components is more flexible.

The invention relates to a digital and physical mixed signature method and device, electronic equipment and a storage medium, and relates to the technical field of information security, and the method comprises the following steps: calculating a document content hash value of an electronic document; obtaining random fiber distribution characteristics of a paper document bearing the electronic document, and generating a paper fingerprint hash value according to the random fiber distribution characteristics; performing data combination on the document content hash value and the paper fingerprint hash value, and performing digital signature processing on the combined hash value data by using a signature private key to generate a composite digital signature; and associating the composite digital signature with the electronic document, and outputting the electronic document for printing, so that the printed paper document is the unique physical entity bound with the composite digital signature. Through the application, an ideal balance can be obtained in three key dimensions of low cost, high safety and convenient verification, and an anti-counterfeiting means which can bind specific paper and can independently and conveniently verify is provided for a common printed piece.

The invention relates to the technical field of smelting element prediction, and discloses an intelligent prediction method and system for the content of residual elements at the smelting end point of a converter. The method comprises the steps that first smelting data and second smelting data are integrated based on heat information, and a historical sample set is generated; screening out sample data belonging to a first threshold interval from the sub-sample set, and combining all the sample data into a standard sample set; key parameters are extracted from the standard sample set, the first content of the converter end point residual elements is calculated based on the initial content and the yield, a label value is set for the standard sample set based on the first content, and a label sample set is generated; summarizing all label sample sets based on the heat information, generating a training data set, constructing a converter end point residual element prediction model based on the training data set, predicting and outputting the residual element content in converter end point molten steel, and adjusting the production process based on the residual element content. According to the method, the residual element content prediction efficiency and precision are improved.

The invention provides a multi-data combined construction site three-dimensional model construction method and system, and relates to the technical field of data processing, and the method comprises the steps: carrying out the calling of a preset resolution satellite image, and obtaining a full-region stereo image pair data set; after radiation correction is carried out, a region surface model and a region elevation model are generated; grid-level modeling defect detection is carried out, and distributed blind area blocks are positioned; performing obstacle avoidance path fitting to generate an obstacle avoidance optimized flight path; the unmanned aerial vehicle is driven to execute multi-angle surrounding scanning, and distributed blind area dense point clouds are directionally collected; constructing a distributed blind area model; and carrying out microscopic superposition, and outputting a three-dimensional model of the construction site. The technical problems that a construction site modeling method in the prior art is limited in the aspects of coverage, modeling efficiency and data real-time performance, depends on a single data source, cannot provide a comprehensive and accurate three-dimensional model of a construction site, and affects the construction progress and decision are solved.

The invention discloses a medical insurance intelligent auditing method and system based on a multi-modal large model, and relates to the technical field of big data processing, and the method comprises the steps: recognizing a material name and a personal name, and auditing the compliance of a material needed for business handling according to the integrity and correctness of the material; identifying first expense detail data according to the expense detail list material and the expense identification cue word; matching the first expense detail data with a medical insurance catalog vector database to obtain a closest catalog entity, and combining the closest catalog entity with the first expense detail data to form second expense detail data; obtaining medicine knowledge from the medicine specification, matching the medicine knowledge with the medical insurance directory vector database, and associating the directory code of the optimal directory entity into the corresponding medicine knowledge; and for each record of the second expense detail data, performing expense rationality auditing according to the corresponding intelligent auditing rule and medicine knowledge. Content acquisition, medical project matching and intelligent auditing of the electronic material are realized, and the auditing speed and accuracy are improved.

The embodiment of the invention provides a page detection method and device, electronic equipment and a storage medium, consistency check, namely static consistency check, is carried out on a field instance corresponding to a first text, then after an action chain is executed, a second text is extracted from a target page corresponding to the action chain, and the second text is extracted from the target page. According to the page consistency detection method and device, the target page is subjected to static consistency detection, the field instance corresponding to the second text is subjected to consistency detection, namely, dynamic consistency detection, the target page is subjected to dynamic consistency detection by executing the action chain, the page consistency detection accuracy is improved, and the page consistency detection efficiency is improved. Through a mode of automatically executing the action chain, the actual operation path of the user is simulated, consistency checking can be carried out in a cross-page mode, the test efficiency is improved, and the problem that the number of test cases is increased due to exhaustive coverage of all possible data combination states is avoided.

The invention relates to a remote health monitoring method and device based on the Internet of Things. The method comprises the following steps: acquiring real-time physiological data and historical health information of a user; determining an individual dynamic threshold interval according to the historical health information; according to the individual dynamic threshold interval, judging whether an abnormal fluctuation data combination exists in the real-time physiological data or not to obtain a judgment result; if the judgment result is that the abnormal fluctuation data combination exists, analyzing the abnormal fluctuation data combination to obtain an analysis result, and obtaining a potential health risk assessment result according to the analysis result; and generating a corresponding health early warning output result according to the potential health risk assessment result. By adopting the method, precise remote health monitoring can be realized, and the false alarm rate and the missing report rate are effectively reduced.

The invention relates to the field of data security, in particular to a data association sensitivity analysis method and system based on a graph attention network, and the method comprises the steps: constructing a knowledge graph based on the features and relationships of various different types of data; stacking the multi-layer graph attention network to obtain dependency relationship weights of nodes in different ranges in the knowledge graph; obtaining sensitivity during data combination based on a preset rule and a correlation model between the data, and performing feature coding and classification on the data combination based on the sensitivity to obtain categories of sensitive risks under different data combinations; performing similarity aggregation on the continuously increased data, and evaluating the uncertainty and sensitivity of data association; comparing the sensitivity with a sensitivity threshold value under a corresponding sensitive risk category to realize sensitivity analysis; according to the method, the complex association relationship of the data can be accurately captured, and compared with a traditional method, the sensitive association discovery rate is increased by 30%-50%.

The invention relates to the technical field of big data analysis and application operation and maintenance, and discloses a multi-data fusion-based application operation and maintenance planning method, which comprises the following steps of: combining multi-source sensor data into a multi-dimensional state vector representing a local space-time state, and comparing the multi-dimensional state vector with a baseline vector representing a normal operation mode to generate a drift vector; according to the method, the stability of the correlation mode in the multi-dimensional data is analyzed, and then the stability of the modulus length and the direction of the drift vector in the time sequence is analyzed, so that potential risks which cannot be perceived by a traditional threshold value mode can be recognized. The focus point of risk recognition is transferred from isolated value out-of-limit to analysis of the stability of the correlation mode in the multi-dimensional data; the early gradual change risk formed by the synergistic effect of a plurality of physical quantities can be effectively identified, and the risk source can be traced based on the analysis process, so that the predictability and decision reliability of operation and maintenance planning are remarkably improved.