66 results about "Automatic Data Processing" patented technology

The invention relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, and a multi-task prediction model based on multi-source historical business chain data training graph neural network and Transform fusion. A plurality of groups of lane layout and event configuration schemes are generated in combination with user real-time operation captured by a design interface, an optimal scheme is screened through simulation evaluation and then is visually displayed, finally, visual lane modeling is executed according to user feedback, and through automatic data processing, high-precision model prediction, real-time interaction optimization and visual modeling, the optimal lane layout and event configuration scheme is obtained. According to the method, the service chain design efficiency and quality are improved, meanwhile, artificial experience deviation is avoided through model prediction based on historical data, the comprehensive requirements of complex equipment development for real-time performance, reliability and resource efficiency are met, and efficient technical support is provided for landing of model-based system engineering in the field of complex equipment.

The invention relates to the technical field of automatic data processing of integrated circuit design, in particular to an automatic parasitic parameter result analysis system based on an FUZZ test. The fuzzy test engine module adopts syntax tree variation to generate a test case library comprising illegal characters, extreme values and logic loops, the exception response module captures illegal operations in an analysis and simulation stage through the probe detection unit, and the correction decision unit executes data restoration or generates an exception report. And the incremental updating unit synchronizes the abnormal features to a model self-optimization module rule base. And the dynamic adaptation module converts the multi-process parasitic parameters into a standardized simulation model through the process parameter abstraction layer. All the modules form a closed-loop system for test case generation, anomaly detection and repair and rule dynamic optimization, automatic processing of an unexpected input scene is achieved, and robustness and multi-process compatibility of parasitic parameter analysis are improved.

According to the rocket flight result rapid evaluation method, rocket flight data can be processed, an interpretation report is automatically generated, and working state rapid interpretation of pre-cooling before launching of a liquid rocket engine, fault diagnosis before ignition and in the flight process is achieved. According to the rapid judgment method for the rocket flight result, the analysis efficiency can be remarkably improved, and the time from the end of rocket flight to the obtaining of the engine analysis result is greatly shortened through automatic data processing, analysis process and rapid report generation. According to the evaluation method, the standard interpretation report is automatically generated, the problems of low manual analysis efficiency, incomplete analysis and the like are solved, and powerful support is provided for evaluation and improvement of rocket launching tasks.

The present application relates to the technical field of automatic data processing, in particular to a dynamic resume evaluation method based on a multi-modal large model. The method comprises: receiving a file containing the resume information of an applicant and a portfolio containing one or more visual works of the applicant; based on the file containing the resume information of the applicant, analyzing the file using a resume analysis module to generate a resume score; based on the portfolio of the applicant, analyzing the portfolio using a portfolio analysis module to generate a portfolio score; based on the file containing the resume information of the applicant and the portfolio of the applicant, calculating a consistency score using a consistency analysis module; and fusing the resume, portfolio and consistency scores to generate a final matching degree score to determine the matching degree of the applicant and the post. The present application solves the problem that traditional methods cannot evaluate visual materials and verify the authenticity of resumes, and provides a more accurate, objective and comprehensive candidate screening scheme.

The application relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, wherein a multi-task prediction model of a graph neural network and a Transformer fusion is trained based on multi-source historical business chain data, a plurality of groups of lane layout and event configuration schemes are generated in combination with real-time operations of a user captured by a design interface, the optimal scheme is selected through simulation evaluation and filtering, and visual display is performed, and finally, visual lane modeling is executed according to user feedback, through automatic data processing, high-precision model prediction, real-time interactive optimization and visual modeling, the design efficiency and quality of a business chain are improved, meanwhile, model prediction based on historical data avoids artificial experience deviation, meets the comprehensive requirements of real-time performance, reliability and resource efficiency for complex equipment development, and provides efficient technical support for the landing of model-based system engineering in the field of complex equipment.

The invention discloses an overflow method substrate glass indentation detection device and a real-time monitoring method thereof, and belongs to the technical field of overflow pull-down method substrate glass manufacturing. The device is composed of a real-time monitoring device, a fixing and position adjusting device, a cooling shell and the like, the indentation width change of annealing furnace opening substrate glass is monitored in real time through image analysis, and automatic processing and early warning of data are achieved in combination with a DCS. The device is light in design, anti-interference and suitable for a high-temperature environment, and a cooling shell ensures stable operation of equipment. The invention provides a safe and efficient detection method, solves the pollution risk and safety problem caused by manual detection, improves the production yield and efficiency, reduces the cost, is suitable for a TFT-LCD substrate glass production line, and has important application value and wide prospects.

The present application relates to a semiconductor factory production data analysis and presentation method and system based on multi-agent cooperation. First, access to multi-source heterogeneous production data and standardization processing. Subsequently, a plurality of serial special ability agents are executed in turn: data agent classifies and stores data; aggregation analysis agent performs cross-system calculation to generate comprehensive indicators; scene recognition agent matches real-time data with preset rules to identify the current running scene; key parameter recommendation agent outputs a sorted key parameter list according to the scene. Finally, the scene, indicators and parameter list are integrated and visualized through a leadership cockpit with natural language interaction function, and can respond to user queries to trigger reanalysis. Through agent cooperation, the present application realizes automatic data processing, scene recognition and dynamic key parameter recommendation, and solves the technical problem of quickly focusing on core production problems from isolated data.

The application provides a complex document intelligent extraction method, system and device based on a multi-modal large model and a storage medium, and relates to the technical field of automatic data processing and information extraction. The disclosed technology provides an efficient, accurate and self-optimizing information extraction solution, which includes a combination of technologies: a two-stage extraction strategy using preliminary screening and deep information extraction balances the efficiency and depth of information extraction; a cross-page dependency graph construction mechanism solves the problem of information fragmentation; a context-aware overall information extraction method ensures that the model reasons in a complete visual context; dynamic task decomposition and dimension reduction techniques are also used to address performance challenges caused by complex tasks; and a prompt word self-optimization closed loop based on artificial feedback is used to achieve continuous learning and precision improvement of the system.

Computerized systems and methods are described for managing vendor-independent configuration-on-order (CTO) and offer-on-order (QTO) processes. A real-time data grid (RTDM) is provided for aggregating, normalizing, and normalizing real-time data from different sources. A single pane view user interface (SPoG UI) facilitates dynamic interaction and visibility to vendor performance. An advanced analysis and machine learning (AAML) module analyzes product compatibility, optimizes a pricing strategy and predicts a market trend. A vendor independent CTO / QTO integration module (VACIM) includes a process standardization engine and a vendor data conversion gateway to ensure consistency of different vendors. According to the method, automatic data processing and data conversion gateway integration are carried out to ensure data consistency, and decision making is carried out by adopting a rule engine driven by machine learning, so that a retailer process is simplified in an extensible and high-adaptability framework, the expandability is enhanced, and a pricing strategy is optimized.

The application relates to a TTV automatic test system and a test method, which comprise a single-channel heating power module, a single-channel temperature acquisition module, a 100-channel power control array, a 100-channel temperature acquisition module array, a system control industrial computer; the single-channel heating power module realizes independent heating control on a single heating unit of a test product; the single-channel temperature acquisition module independently acquires temperature signals of corresponding areas; the 100-channel power control array and the 100-channel temperature acquisition module array realize centralized management and synchronous control on more than 3000 heating channels and temperature acquisition channels. Through multi-channel power array control, array type temperature acquisition and industrial bus centralized control architecture, the application realizes controllable and adjustable heating power, real-time temperature acquisition and automatic data processing, improves data acquisition density, supports millisecond-level transient temperature acquisition, improves test efficiency and reduces test cost.

The invention discloses an SF6 multi-component mixed gas liquefaction temperature detection method and system based on a laser scattering method. The system comprises a high-pressure visual cavity, a temperature and pressure control system, a laser light source, an optical signal detection system and a data acquisition and processing unit. The design of the high-voltage visual cavity simulates the working condition of actual electrical equipment, and the measurement result has higher engineering reference value; non-contact measurement is realized by means of optical detection, and subjectivity of manual observation in a traditional method is avoided; the automatic data processing flow improves the measurement efficiency and repeatability, and is especially suitable for continuous monitoring requirements of multi-element mixed gas. The method provides a reliable technical scheme for solving the practical problem of SF6 mixed gas liquefaction temperature monitoring in power equipment.

The invention discloses a steel wire rope intelligent detection crawling robot and a detection method thereof. The steel wire rope intelligent detection crawling robot comprises a robot frame and a robot body. The robot body comprises a detection probe assembly, a plurality of crawling roller assemblies, a driving control unit, a data processing unit, a power supply unit module, an encoder assembly and a safety rope ring assembly, the driving control unit is used for controlling the crawling roller assemblies to crawl along a to-be-detected steel wire rope, and the detection probe assembly is used for conducting magnetic flux leakage detection on the to-be-detected steel wire rope; the data processing unit is used for collecting, analyzing and storing magnetic flux leakage detection data, the power supply unit module is used for supplying power, and the encoder assembly is used for obtaining crawling data of the robot body; the safety rope ring assembly is used for being connected with a safety rope to prevent the robot body from falling from the to-be-detected steel wire rope. Through intelligent detection, automatic data processing and data storage in the autonomous crawling process, intelligent detection of damage of the steel wire rope is achieved.

The invention discloses an intelligent prediction method and system for operation platform operation and maintenance data, and the method comprises the steps: firstly, widely collecting all kinds of operation platform operation and maintenance data closely related to a prediction object, and carrying out the cleaning and preprocessing of the collected data; secondly, for the processed data, automatically extracting features with key value for a prediction task from the original data through a machine learning algorithm; then, on the basis of the extracted data features and a specific prediction target, a prediction model is constructed on the basis of a machine learning algorithm; training the prediction model by using historical data to obtain a trained prediction model; inputting new operation and maintenance data into the trained prediction model for prediction and evaluation; and finally, performing real-time response processing on the generated prediction result. According to the scheme, the intelligent prediction model for the operation and maintenance data of the operation platform is formed based on fusion of automatic data processing and a machine learning model, and efficient and accurate prediction for the operation and maintenance data generated by the operation platform can be realized.

The invention provides a real-time monitoring and processing method and system for impact resistance test data of foam concrete and application, and relates to the technical field of material detection.The method comprises the steps that a high-speed camera collects a process image of a drop hammer impact foam concrete test block in real time, and image data is transmitted to a control end; the control end identifies the position of the drop hammer relative to the leveling rod in each frame of image in the process image, calculates the impact depth of the drop hammer and determines the impact time of the drop hammer; according to the impact depth and the impact time, the impact speed and the impact energy of the drop hammer are calculated; based on the change relation of the impact speed, the impact energy and the impact depth, an impact response curve is generated, and the impact resistance parameters of the foam concrete are output. According to the method, the impact process can be accurately monitored in real time, quantitative and objective impact resistance parameters are output through automatic data processing, and the problem that in the prior art, a method for quantitatively testing the impact resistance of foam concrete is lacked is solved.

The invention relates to the technical field of visual media data backup, and discloses a visual media data backup method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the information of each high-speed write-in port and a common port through main equipment, and interacting with a specified terminal through a user-defined protocol, and then, on the basis of a write-in scheme generated by the reading instruction, a personalized processing scheme is formulated for each piece of to-be-backed-up data to ensure that the data is backed up. The method has the advantages that the data backup and transmission efficiency is improved through the user-defined protocol, the increasing image and video data requirements are met, compared with a traditional manual backup mode, the automatic data processing flow is provided, and the data loss or damage risk caused by manual operation is remarkably reduced.

The invention relates to the technical field of three-dimensional modeling, and particularly discloses a method and system for quickly generating a building three-dimensional white model, and the method comprises the following steps: obtaining an image region range, and determining a target region in a manner of manually dragging a base map of a map and inputting a place name or latitude and longitude coordinates by a user; extracting the contour of the building and obtaining space coordinate information, analyzing the remote sensing image of the target area by using an AI image recognition algorithm, automatically extracting the contour information of the building, and reading the corresponding space coordinate data to obtain the contour data of the building; and cleaning the contour data, endowing the contour data with a height value, and cleaning the extracted building contour data. Through an AI image recognition algorithm and an automatic data processing flow, the generation time of the building three-dimensional white mold is greatly shortened, and the problem that a traditional method is long in consumed time is solved.

The application provides a ship voyage track generation method based on STK and MATLAB combined simulation, comprising: setting a random seed, initializing an STK environment through MATLAB, and loading a set simulation scene; under the simulation scene, randomly selecting a ship model needing to be simulated, and setting a corresponding type, attribute and speed for each ship model; using a random algorithm to generate a starting point and an ending point of each ship model, using an interpolation method to generate continuous and diverse path points, and through dynamic propagation of the path points, updating a voyage track of the ship model in real time. The application not only improves the efficiency and practicability of the voyage track simulation, but also greatly improves the convenience and accuracy of the voyage track data analysis through automatic data processing and output functions, and is suitable for fields of ocean research, navigation safety evaluation, channel planning, military and education training and the like.

The invention relates to an automatic data processing method and system. The method comprises the following steps: S1, constructing an ETL task generation rule base; s2, automatically generating an ETL task according to a user request; s3, deploying and executing an ETL task; and S4, performing configuration information persistence and state monitoring feedback. According to the method, the ETL task generation rule base can be constructed to realize logic rule solidification, the XML file is automatically generated, deployed and executed according to a user request, meanwhile, the information is persistently configured, the task state is monitored, automatic generation, execution and log monitoring of the ETL task are realized, end-to-end and whole-process ETL templating and automation are realized, and the efficiency is improved. The problems of repeated configuration, high technical threshold and lack of intelligent multiplexing in a traditional development mode are solved, and the method has the advantages of improving the development efficiency, reducing the error rate and enhancing the deployment standardization degree.

The invention relates to the technical field of data processing, in particular to an automatic data processing system and terminal equipment, and the system comprises a multi-source data collection module which is used for collecting a multi-source data by using a preset dynamic start-end time screening strategy and employee basic information obtained from a first structured database; screening historical attendance data obtained from the second structured database to obtain effective attendance data; the identification module is used for identifying the shift type of each employee in the effective attendance data according to the week characteristics and the on-off time characteristics; the data integration module is used for integrating each piece of employee information, the corresponding shift type and the corresponding effective attendance data in the employee basic information to obtain to-be-processed employee information; the determining module is used for determining follow-up personnel corresponding to each shift type in the target shift arrangement period from the to-be-processed employee information according to the position requirements and the multi-rule cooperation principle, and generating a shift arrangement table, and the problems of low shift arrangement efficiency, poor reasonability and poor adaptability can be solved.

The invention provides a complex document intelligent extraction method, system and device based on a multi-modal large model and a storage medium, and relates to the technical field of automatic data processing and information extraction. According to the technology disclosed by the invention, an efficient, accurate and self-optimized information extraction solution is provided, and the method comprises a group of technical combinations: a two-stage extraction strategy of preliminary screening and depth information extraction is utilized to balance the efficiency and depth of information extraction; the problem of information fragmentation is solved by utilizing a cross-page dependency graph construction mechanism; a context-aware overall information extraction method is utilized to ensure that the model carries out reasoning in a complete visual context; a dynamic task decomposition and dimension reduction technology is utilized to deal with performance challenges brought by complex tasks; and a cue word self-optimization closed loop based on manual feedback is utilized, so that continuous learning and precision improvement of the system are realized.

The invention discloses a method for automatically searching a crane station, which belongs to the technical field of cranes, is used for crane station selection, and comprises the following steps: carrying out preliminary selection on the crane station according to vectorized field photogrammetric data to obtain a selectable set of the crane station; detecting the feasibility of the optional set of the filtered crane stations on the basis of the field site cloud data to obtain feasible crane stations, and performing collision check detection during secondary hoisting on each feasible crane station on the basis of the field site cloud data and crane parameters in the feasible crane stations to obtain a unique feasible crane station. According to the method, a standardized decision-making model and a quantitative analysis system are established, so that the dependence on personal experience is effectively reduced, and the scientificity and consistency of a station scheme are improved; automatic data processing and an intelligent algorithm are adopted, site parameters and equipment information are rapidly analyzed, and the scheme making period is greatly shortened.

The invention relates to the technical field of agriculture, and discloses an intelligent agricultural greenhouse environment monitoring system, which comprises an intelligent sensor, monitors indoor environment parameters of an agricultural greenhouse in real time, collects environment parameter data, calculates an environment state index and a sensing induction index based on the environment parameters, and sends the environment state index and the sensing induction index to the intelligent sensor. And the display module is used for displaying the environmental parameters collected by the intelligent sensing module and the calculation results of the environmental state indexes and the sensing induction indexes, extracting the environmental state indexes and the sensing induction indexes to judge the current environmental state and the current sensor state, and sending out feedback signals. The system constructs a comprehensive environment monitoring system for environment monitoring of the greenhouse, guarantees comprehensiveness, real-time performance and accuracy of environment parameter monitoring through multi-sensor cooperative acquisition and automatic data processing, avoids hysteresis and errors of manual monitoring and decision errors caused by monitoring failure, and improves the monitoring efficiency. The labor management cost is greatly reduced, and the intelligent and refined management level of agricultural greenhouse planting is improved.

The invention relates to the field of mineral resource evaluation, in particular to a mineral economic value prediction method based on multi-source data fusion. Comprising the following steps of data collection and analysis, representative drill hole selection, rapid detection data acquisition, key segment chemical analysis, data verification model construction, historical data reliability evaluation, ore body spatial feature analysis, resource quantity re-verification and grading and economic value dynamic prediction. Through a multi-source data fusion and intelligent analysis technology, existing exploration and production data are fully utilized, and dependence on newly added field exploration is reduced; a representative sample grading collection and intelligent space modeling method is adopted, the precision of resource reserve assessment is effectively improved, the assessment process is accelerated through an automatic data processing platform and a dynamic feedback mechanism, the problem of data reliability and cost-benefit balance in undeveloped mine right assessment is solved, and the method is suitable for popularization and application. And a scientific basis is provided for mine right circulation and resource development.

The invention discloses an unmanned aerial vehicle intelligent receiving party system considering highway engineering project receiving party rules, and belongs to the technical field of constructional engineering, the system is used for uploading basic data through a preparation center module, the basic data comprises an organized road center line, a designed cross section and a construction red line, regulation setting can be preset, and the design cross section and the construction red line can be preset; subsequent data processing conforming to rules is facilitated; the processing center module is used for uploading and processing the picture data uploaded by the unmanned aerial vehicle, can realize remote and unmanned data acquisition, is suitable for an engineering environment, and can reduce the cost; and the application center module is used for carrying out business operation on the scene unit, scenes corresponding to the scene unit comprise original ground remeasurement, roadbed earthwork calculation amount and plotting receiving amount, automatic data processing can be provided, and the data processing efficiency is improved.

The application discloses a kind of MEMS accelerometer nonlinearity batch testing device and method, including test tooling, the test tooling is fixed on centrifuge, and install multiple MEMS accelerometers on test tooling, each MEMS accelerometer is connected to the input end of multichannel analog-digital converter respectively, is converted into digital signal, and the digital signal output by analog-digital converter sequentially passes through microcontroller, serial port level conversion chip and is converted into serial port data.The application installs test tooling on test station, increases the number of testing devices, converts device output signal and the mode of automatic data processing improves test efficiency, reduces test cost, realizes single multiple devices synchronous testing, positive and negative synchronous testing batch testing mode.The application is divided into two kinds based on MEMS accelerometer sensitive axis, designs two different test toolings, to adapt to different MEMS acceleration test.

The invention discloses a method, a system, equipment and a medium for automatically acquiring atmospheric stability joint frequency, relates to the technical field of data analysis, solves the technical problem that the acquisition efficiency and accuracy of the atmospheric stability joint frequency are not high enough, and provides a conformity data screening method and an automatic data management method. The method comprises the following steps of: cleaning data, matching the data, performing data screening on the data which cannot be successfully matched according to the correlation and logic distance between the data to be judged and known data, and performing treatment based on the data, which is different from the existing data processing in a manual mode; the system has the beneficial effects of full-automatic data processing, high-precision data screening, high-efficiency data management, human error prevention and the like.

The multivariate heterogeneous data integration method about the smart city comprises the following steps that S1, data sources are configured and connected, and a user carries out database configuration according to different data sources; s2, accessing a data acquisition standard module, and performing automatic data processing and verification; and S3, writing the data into a data warehouse of the big data platform through the platform integration task. The invention provides a multivariate heterogeneous data integration method for a smart city. The method can perform semi-automatic data cleaning and perfect data standards according to pre-collected data. For a smart city, the smart city relates to many industries, and the storage of the same type of data of different data sources can be merged, classified and unified through the method. Clean and normative data are provided for subsequent big data processing analysis, artificial intelligence training data and the like, and analysis accuracy and algorithm fitting are improved.

The invention discloses a bridge point cloud data automatic extraction and elimination method and system based on a river center line, and relates to the technical field of point cloud data processing, and the method comprises the following steps: building an automatic data processing flow, remarkably reducing the demands of manual intervention, and improving the efficiency of point cloud data processing. The method comprises the steps of data acquisition, preprocessing, feature extraction and elimination, adopts an intelligent algorithm and a data processing technology, achieves efficient and automatic point cloud data processing, and solves the problems that an existing point cloud processing technology is low in efficiency, insufficient in precision and much in manual intervention in a complex water area and bridge intersection area.

The invention relates to a big language model data conversion method and system based on model structure analysis, and belongs to the technical field of automatic data processing and artificial intelligence. Aiming at the problem that a simulation model is stored in a binary format and is difficult to directly understand by a large language model, the invention provides a conversion method for automatically analyzing structural data of the simulation model and generating a structured text. The method comprises the steps of reading a model file, analyzing a component structure and a connection relation in a model, tracking variable references and replacing the variable references with corresponding actual values, and further generating a structured document adaptive to a context window of the large language model. Through the technical scheme, the large language model can understand and reasone the simulation model, the simulation analysis efficiency is improved, manual intervention is reduced, and the method is suitable for application scenes such as power electronics, control system design and fault diagnosis.

The invention discloses a temperature control process diagram batch generation method and system, and belongs to the field of glass manufacturing, and the method comprises the steps: setting a column title of a temperature control process table according to the type of temperature control process data, and obtaining the temperature control process table; importing the temperature control process data into a temperature control process table; and generating temperature control process diagrams in batches based on the data in the temperature control process table. Compared with a traditional rapid method for manually generating the temperature control process diagram, the automatic data processing mode is adopted, interference and errors of human factors are reduced, and the speed and accuracy of generating the temperature control process diagram are improved.