92 results about "Automated data processing" patented technology

The present disclosure provides a method and system for orchestrating automated data processing and transformation. A centralized orchestrator receives a request to process a client dataset and initiates a data ingestion process to obtain sample data. A semantic analysis module analyzes the sample data to determine semantic types of data fields. A transformation module generates data transformation instructions based on the determined semantic types. The orchestrator deploys a data processing pipeline to a client-controlled environment and configures privacy preservation parameters to identify and obfuscate potential personally identifiable information. The pipeline applies the transformation instructions and privacy parameters to the dataset. A configuration module determines data storage configurations for the transformed dataset. The transformed dataset is stored according to the configurations in a client-controlled or cloud environment. A machine learning module generates a model based on the transformed dataset, which is stored in a model repository accessible to the client.

The present invention relates to a method for automated data processing to assess the state of multiple filtration membranes used in liquid filtration. The method involves receiving data from state sensors positioned within or near a set of membranes, which process incoming water into permeate and concentrate flows. This data, collected as time series at predefined frequencies, pertains to external physical parameters. An operating indicator is determined from this data, forming a second time series. Both the first and second time series are recorded as point clouds over a specified acquisition period. An intermediate operating indicator is generated, representing the state of new, clean, or cleaned membranes, using a learned normalization model. Finally, a normalized operating indicator is produced, characterizing membrane fouling and aging, independent of environmental variations, and forming a third time series. This method enhances the accuracy of membrane state assessment in filtration systems.

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 provides an automatic data processing method and device based on enzyme-linked immunosorbent assay, a medium and electronic equipment. The automatic data processing method comprises the following steps: obtaining type data, subordinate set number and test sequence of each to-be-tested sample in a plurality of sets of to-be-tested samples corresponding to a plurality of worktables of a source file; acquiring absorbance values in a plurality of worktables of the source file; filling a calculation template with the type data, the test sequence numbers and the absorbance values of the to-be-tested samples, and performing logarithmic linear regression analysis calculation to obtain calculation result data corresponding to each to-be-tested sample; and inputting the calculation result data into a summary template to generate a summary table, and identifying the calculation result data in the summary table according to the data state. By adopting the automatic data processing method provided by the invention, the test data can be efficiently, automatically and accurately processed, and meanwhile, the risk of errors in the data processing process by workers is avoided.

The invention discloses a standard information physical examination table intelligent verification method and system based on data automation, and the method comprises the steps: generating standard candidate data of a target field through a data collection step and data standardization processing, and carrying out the screening, and obtaining a standard data set; determining the dependency relationship between the fields of the physical examination table, mapping the standardized data values to the corresponding positions of the fields of the physical examination table through a field mapping function, and generating the physical examination table through data verification and automatic correction; analyzing the relationship between the fields of the physical examination table to predict and generate a filling suggestion value, and generating a filling suggestion list through regularization item correction and verification; inputting the physical examination table data input and modification of the doctor, and generating a final physical examination table draft; and performing consistency verification and medical compliance verification on the final physical examination table draft to generate a formal physical examination table. Through data integration, structured mapping and context reasoning filling, the filling efficiency, data integrity and medical compliance of the physical examination table are improved, and the workload of doctors is relieved.

The invention discloses a photovoltaic array deformation monitoring method, system and device and a medium. The method comprises the following steps: acquiring photovoltaic array information; dividing and marking the photovoltaic array based on the photovoltaic array information; based on the mark, performing image recognition on the photovoltaic array by using an image recognition algorithm to obtain coordinate data of the photovoltaic module; and according to the coordinate data, calculating to obtain a central point coordinate of the photovoltaic module, and comparing the central point coordinate with a standard coordinate to obtain the deformation size of the photovoltaic array. A monitoring device does not need to be installed on each photovoltaic module, the large-scale monitoring cost is greatly reduced, meanwhile, the monitoring efficiency is improved through multi-view image recognition and automatic data processing, hidden dangers such as support deformation and foundation settlement can be found in time, the risks of power generation efficiency reduction and square matrix collapse are effectively avoided, and the method is suitable for popularization and application. And an intelligent and high-precision solution is provided for safe and efficient operation and maintenance of a photovoltaic power station.

The invention discloses an intelligent early warning method and device for low-code development and a medium, and relates to the technical field of software development. The method comprises the following steps: acquiring historical monitoring data through a multi-source data interface, and pre-training a time sequence prediction model loaded in an artificial intelligence platform based on the historical monitoring data; creating a data acquisition form in the low-code platform, and establishing an automatic data processing flow through a flow engine; when a form data submission event is detected, a model reasoning service calling instruction is triggered, so that current monitoring data and corresponding historical time sequence data are input into the time sequence prediction model, and a prediction value of a future time period is obtained; wherein the historical time sequence data is historical monitoring data within a preset duration before the current monitoring data is obtained; and comparing the predicted value with an actual monitoring value after a future time period, and if the deviation exceeds a preset threshold value, sending an alarm notification based on a preset alarm mechanism.

The application discloses a kind of intelligent park infrastructure intelligent monitoring system, it is related to the technical field of intelligent monitoring, including fusion module, prediction module and optimization module, set state related parameter, characteristic data is obtained by fusion, state prediction model is obtained by training, state prediction model is optimized.The application fusion module fuses the characteristic value of multiple state related parameters, reduces the complexity and delay of data processing, improves the monitoring efficiency through automated data processing and model optimization, the characteristic value of multiple related parameters is fused by fusion module, avoid the limitation of single parameter, optimize state prediction model, can dynamically adjust model parameters according to actual operation data, further improve the prediction accuracy of model, can early warning potential failure risk, take measures in time to maintain and repair, reduce the probability of failure occurrence, improve the reliability and stability of power supply facilities.

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 a mobile vibration exciter capable of automatically positioning, and relates to the field of vibration testing. The motor drives the cam shaft to drive the knocking hammer to swing, the torsional spring is connected with the driven wheel shaft and the swing rod, the pre-torsion of the torsional spring is changed by adjusting the angle of the swing rod, accurate knocking and rapid resetting of the knocking hammer are achieved, and secondary knocking is avoided. A single-chip microcomputer controls rotation times and frequency of a motor through programming, and a two-axis servo system or a mechanical arm is combined with a visual identification technology to automatically generate a surface knocking grid of a measured object and drive a vibration exciter to move to a specified point according to a program; the NI data board card and the acceleration sensor collect vibration signals, the Labview test software analyzes a frequency response function, a phase curve and a damping value in real time, automatically extracts a peak value, generates a test report, and supports mistaken touch prevention alarm. The technical problems that an existing vibration exciter cannot automatically adjust the knocking force and cannot achieve full-modal measurement and automatic data processing are solved, and the testing efficiency and precision are remarkably improved.

The present invention belongs to the technical field of traditional Chinese medicine assisted diagnosis and treatment, and specifically discloses an assisted diagnosis and treatment system based on a traditional Chinese medicine large model. By receiving tongue image uploaded by patients at the same time period regularly, tongue image features of different tongue body regions are extracted. Thus, by using the tongue image features under time series, tongue image change curves are generated, and the syndrome type evolution path is output by using the tongue image - syndrome type model. Then, the clinical indicators of the patients in the same time series are associated with the syndrome type evolution path to form a syndrome type - disease association matrix. Based on this, a prescription compatibility scheme is recommended to ensure that the treatment plan is not only based on the syndrome type, but also fully considers the specific pathological mechanism and clinical manifestations, avoiding the disconnection between the treatment plan and the actual condition, realizing more accurate and personalized traditional Chinese medicine assisted diagnosis and treatment. In addition, automated data processing and analysis reduce manual intervention, improve the diagnosis and treatment efficiency, and save medical resources.

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 continuous casting roller water flow detection method and device for off-line maintenance of a continuous casting machine, and relates to the technical field of mechanical manufacturing, the device comprises a base and a continuous casting roller body, a U-shaped plate is arranged above the base, extension supporting plates are arranged on the side edges of the top ends of vertical sections of the two sides of the U-shaped plate, and supporting structures and fixing assemblies are arranged at the upper ends of the two extension supporting plates; movable adjusting assemblies are connected to the lower ends of the two extending supporting plates, a leveling sensor is fixed to the upper end of the horizontal section of the U-shaped plate, a water tank is arranged at one corner of the side of the upper end of the base and connected with a flow measuring assembly, and a detection host is fixed to the upper end face of the base. According to the invention, high-precision measurement is realized, and the water flow performance of the continuous casting roller is accurately evaluated; the continuous casting roller is easy to mount and dismount; data processing is automatic, and the detection efficiency and accuracy are improved; the detection requirements of continuous casting rollers of different specifications can be met; and the off-line maintenance and detection quality of the continuous casting roller is improved, so that the service life is prolonged.

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 present invention relates to the technical field of operation and maintenance management, and specifically relates to an integrated operation and maintenance management system and method based on AIOps; the method includes: collecting multi-source IT operation and maintenance data and completing standardized preprocessing to form operation and maintenance data input in a unified format; classifying and storing the preprocessed data using a hybrid storage architecture, and implementing data synchronization through a cross-database synchronization tool to break data silos; performing intelligent analysis on the data based on the TensorFlow framework to generate fault diagnosis results and performance trend prediction data; generating operation and maintenance decisions according to the analysis results, and performing automatic repair, work order allocation or resource scheduling operations; outputting operation and maintenance management results, presenting data and decision execution situations through a visualization interface, and providing report generation and management configuration functions; through a full-process automated data processing and intelligent operation and maintenance decision-making mechanism with multi-module collaboration, the technical problems of slow fault response, weak data integration, low accuracy of risk prediction and low operation and maintenance efficiency in the traditional operation and maintenance mode are solved.

Systems, methods, and devices for automating data processing tasks that typically rely on specialized software without API-level access. A virtual machine environment may be created on a cloud server for automated interaction with a target software application. Configuration instructions specifying one or more automation tasks for execution within the virtual machine environment may be received. Automation tasks may be executed within the virtual machine environment by emulating user interactions with the target software application. Data generated by the target software application may be received in response to the emulated user interactions and an execution status associated with the one or more automation tasks may be determined based on the received data. The execution status may be transmitted to a designated external system.

This invention discloses a method for rapidly extracting and classifying interglacial lakes in the Antarctic Cosmonaut Sea. The steps include: quality control of sea ice concentration data, identification and extraction of interglacial lakes, classification of interglacial lakes, and data storage. This method improves the speed and accuracy of extracting spatial distribution, spatial morphology, and area parameters of interglacial lakes. It enables the extraction of interglacial lakes by category, facilitating research on the formation mechanisms of different types of interglacial lakes. It also improves the degree of automated data processing, reduces manual intervention and workload, standardizes data processing criteria, improves data quality, and obtains long-term data sequences. Furthermore, it helps researchers to promptly grasp the near-real-time status of interglacial lakes during the sea ice growth season (May-August) in the Antarctic Cosmonaut Sea, enhancing understanding of the formation and dissipation processes of interglacial lakes, further strengthening scientific understanding of the Cosmonaut Sea, providing data support for future scientific expeditions, and serving my country's national strategic interests in Antarctica.

The invention discloses a flue-cured tobacco purchasing system based on process reconstruction, and the system comprises a hardware layer which is used for collecting, transmitting and processing physical information related to tobacco leaf purchasing; the software layer is used for processing, storing, analyzing and managing data, ensuring that the data is smooth and accurate in the purchasing process, and generating related records and reports; the process layer is used for defining operation steps and data flow paths from the beginning to the end of tobacco leaf purchasing, automation of the tobacco leaf purchasing process is systematically achieved by integrating the RFID technology, the weighing equipment and an automatic data processing module, manual intervention is greatly reduced, the purchasing efficiency is improved, subjective factors and personal emotion of weighing personnel are weakened, and the weighing personnel can conveniently purchase tobacco leaves. The fairness of the transaction is ensured; grade information and weighing data are automatically associated, errors and omission caused by manual input are reduced, and the accuracy and integrity of the data are ensured; the use of the RFID tag ensures the accurate recording of tobacco leaf grade information, and the tobacco leaf grade information is easy to track and query.

This application discloses a quality inspection and appeal method, apparatus, electronic device, and storage medium, relating to the field of automated data processing technology. The method includes: receiving a quality inspection plan task request configured by an operations planning platform; obtaining object data according to the quality inspection plan task request; uploading the object data to an analysis platform and receiving the quality inspection results returned by the analysis platform; and, in response to detecting a violation in the quality inspection results, initiating a quality inspection appeal process through the operations planning platform. This application can reduce labor costs and unify, automate, and standardize the quality inspection and appeal process.

The invention discloses an automatic processing system and method for electric power information communication scheduling operation data. The system comprises a man-machine interaction module, a data capture module, a report processing module, a file management module and a data verification module. The man-machine interaction module is used for realizing data interaction between the system and an operator; the data capturing module is used for automatically extracting work order data through a cross-communication scheduling core business system; the report processing module is used for realizing monthly report updating, daily report generation and end-of-month data archiving; the file management module is used for managing template files, result files and log files related to the system; and the data verification module is used for verifying the accuracy of the data processing result. The method disclosed by the invention is high in data processing efficiency, good in integrity and relatively high in accuracy.

The invention discloses a remote sensing big data automatic processing method based on cloud computing, and relates to the field of remote sensing big data processing, and the remote sensing big data automatic processing method comprises the steps: (S1) collecting remote sensing data; (S2) uploading remote sensing data to a cloud computing platform; (S3) processing and analyzing the remote sensing data by adopting a cloud computing processing model; (S4) storing the remote sensing data compression package to a cloud computing platform, and debugging a data processing algorithm by adopting a container cloud integrated model; (S5) displaying and analyzing a processing result by adopting a data visualization platform; according to the invention, remote sensing big data automatic processing is realized based on cloud computing, and a low-orbit remote sensing constellation-oriented transmission routing task planning algorithm and a container cloud integrated model are fused at the same time, so that the efficiency and security of remote sensing big data automatic data processing and data transmission are improved.

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 embodiment of the invention discloses a picture document cross-page table merging method and device and related equipment. The method comprises the following steps: disassembling a picture document into independent pages with the same size, and arranging the independent pages according to page numbers to obtain a page set; performing header identification on the next page of the two adjacent pages in the page set through a pre-trained header identification model, and determining whether the next page of the two adjacent pages has a header or not; if the header exists, judging whether the header of the next page of the two adjacent pages is consistent with the header of the previous page or not, if the headers are consistent, removing the header of the next page, and merging the bodies of the two pages; if the headers are inconsistent, not carrying out merging processing; if the header does not exist, judging the column numbers of the table bodies of the two adjacent pages, and carrying out merging judgment; and if the column numbers of the table bodies of the two adjacent pages are different, not merging. According to the method, whether complex cross-page tables are combined or not is judged, and automatic processing of data is promoted.

According to the automatic data processing system and method based on artificial intelligence, a client provides inquiry information to an artificial intelligence platform, so that the inquiry information is provided to a large language model through a decision agent to generate at least one task and select a corresponding task agent; the task agent executes the selected task to generate a task result and a task completion instruction and feeds back the task completion instruction to the decision agent, the decision agent selects the task agent corresponding to the continuous task, and the answer agent generates an answer result from the task results of all the tasks by using an artificial intelligence generation technology and feeds back the answer result to the client; therefore, the technical effect of providing convenient and automatic data processing based on artificial intelligence can be achieved.

This application discloses a tunnel damage monitoring method and system, belonging to the field of data processing technology. The method includes: acquiring tunnel operation data and tunnel damage data, and transmitting them to a control center; creating a scoring dataset; creating a damage dataset; constructing a tunnel damage monitoring model, training the damage monitoring model until a standard is met; continuously collecting real-time tunnel operation data, inputting the real-time tunnel operation data into the tunnel damage monitoring model to obtain a real-time damage score; if the real-time damage score exceeds a preset damage score threshold, the real-time tunnel damage data is determined through the tunnel damage monitoring model. This solution can promptly detect potential damage or anomalies, ensuring tunnel safety. Automated data processing using a model improves data processing efficiency. By analyzing historical and real-time data, the model captures patterns and trends in real-world situations, ensuring that the results match the actual situation and improving the reliability of the analysis results.

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 present invention discloses a simulation test system and simulation test tool for a universal printer, comprising an intelligent test control module, a modular test module, an automatic data processing module and a remote control assistance module; the intelligent test control module automatically selects and adjusts the test strategy according to the test requirements, thereby realizing the intelligent management of the test process; the modular test module quickly reconfigures the test tool according to different test requirements, thereby improving the flexibility and adaptability of the test; the automatic data processing module automatically collects, analyzes and stores test data, generates test reports, and improves the efficiency of data processing; the remote control assistance module supports personnel in accessing and controlling the test system, performing fault diagnosis and maintenance, and adopts advanced test technology and intelligent control strategies, thereby realizing the automation, intelligence and efficiency of the test process, improving the test quality, reducing the cost, and providing strong support for the continuous improvement and optimization of the printer.