115 results about "Automated data processing" patented technology

The invention belongs to the technical field of information, and relates to a multi-level dynamic intelligent automatic data processing and information evaluation method and system. The method comprises the steps that a database environment operation data set is constructed, targeted training and fine adjustment are conducted on a large language model in combination with reinforcement learning, and full-automatic data analysis, query and information extraction of multiple tables in a database are achieved; a multi-level agent interaction and cooperation framework is established, a scheduling agent is responsible for global decision making and strategy planning, an operation agent is responsible for execution of specific tasks, and the scheduling agent and the operation agent share information and coordinate the tasks to form a highly cooperative whole; and establishing a cyclic supervision and error correction mechanism, scheduling the intelligent agent to learn a normative workflow example of the target working environment and track the state of the operation intelligent agent in real time, identifying the behavior of the operation intelligent agent deviating from a predetermined path, and taking corrective measures. According to the method, high efficiency, intelligence and automation of data processing are realized, and the method has remarkable practical value and innovative significance.

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 invention relates to the technical field of calibration test, and particularly discloses a strapdown inertial navigation automatic calibration test method of a temperature control biaxial rate position turntable. Comprising the following steps: S1, multi-dimensional error modeling and layered calibration architecture: constructing a comprehensive error model containing a sensor scale factor error, an installation non-orthogonal error, a zero offset error, a cross axis coupling error and a temperature related error; s2, a wide temperature range self-adaptive compensation mechanism: carrying out heat preservation at a preset temperature point and executing turntable positioning and rate movement; s3, performing automatic data processing and parameter estimation; and S4, performing real-time error correction and dynamic verification: performing real-time error correction based on the estimated parameters, and evaluating navigation performance indexes such as position, speed and attitude precision. Through technical innovation, high-precision, automatic and wide-temperature-range calibration of the strapdown inertial navigation system is realized, and the method is suitable for aerospace, intelligent equipment and other scenes with strict navigation precision requirements, and has remarkable engineering application value and market competitiveness.

The invention relates to the technical field of environment monitoring, in particular to an underground water monitoring and early warning method and system based on multi-source data fusion, and the method comprises the following steps: obtaining water quality, flow velocity, temperature and pH value data, adjusting the collection frequency, verifying the state of a sensor, forming a water quality and geologic feature data set, analyzing rainfall, air temperature, permeability and water flow dynamic state, and obtaining a water quality and geologic feature data set. And generating a seepage trend, identifying a pollutant diffusion path, range and main path, evaluating a diffusion rate and influence, and generating a pollution diffusion early warning level in combination with permeability and risk standards. According to the invention, through fusion analysis of multi-source data, determination of the correlation between an underground water flowing mode and water quality change, timely capturing of the influence of meteorological change on underground water, accurate evaluation of pollutant diffusion path, rate and influence range, improvement of timeliness and accuracy of pollution early warning, and improvement of monitoring response speed through automatic data processing. And timely and accurate decision support is provided for groundwater resource management and pollution control.

The invention is suitable for the field of data processing and analysis, and provides a medicine cold chain on-line fast verification system and a real-time data processing and intelligent analysis method thereof.The medicine cold chain on-line fast verification system has the beneficial effects that the medicine cold chain on-line fast verification system comprises a wireless temperature and humidity recorder, an intelligent management host and upper computer server platform software, and the wireless temperature and humidity recorder adopts an SHT40 sensor; the wireless management host receives encrypted data of the recorder, then transfers the encrypted data to the W25Q256JVEIQ storage chip, and encrypts and uploads collected environment parameters and equipment state information to the upper computer server, an online real-time verification technology is introduced, instant monitoring and response to overtemperature early warning can be achieved, rapid deviation correction can be achieved, repeated verification of traditional offline verification is avoided, and the verification efficiency is improved. And the verification period is greatly shortened. The automatic data processing system realizes full-chain unmanned intervention, reduces manual operation time, guarantees data authenticity, and improves verification efficiency and result objectivity.

The invention relates to the technical field of task management, and discloses a laboratory automatic data processing and management method, system, equipment and medium, and the method comprises the steps: obtaining the equipment information and resource information of a laboratory; and establishing an equipment simulation model of the laboratory. A task instruction is collected, and the task instruction is disassembled into atomic tasks. And arranging the execution sequence of the atomic tasks according to the inherent sequence constraint of the task instruction, the maximum resource utilization rate, the minimum scheduling frequency and the comprehensive analysis result of the optimal working time of the equipment. And performing task execution by using the execution sequence of the atomic tasks. Idle and faults of equipment are effectively avoided, resource waste is reduced, and automation and accuracy of experimental operation are improved. Besides, by analyzing the working time of the equipment and the validity period of the consumables, the energy consumption and the operation cost can be reduced while the smooth proceeding of the experiment is ensured, and the automatic management level of the laboratory is further improved.

The invention discloses a large model enhanced telephone fraud high-risk user identification method and system, and relates to the technical field of artificial intelligence and information security. The objective of the invention is to improve the accuracy of telephone fraud identification by means of multi-level automatic data processing, multi-model training optimization and multi-model probability fusion, and can significantly reduce the calculation cost and resource consumption. According to the technical key points, a multi-dimensional feature system is constructed by analyzing call data of a user; through multi-model training optimization, high-risk probabilities of different models for different users are obtained, multi-level features of user behaviors are deeply mined, and a machine learning model, a deep learning model and a large language model are covered; the output probability values of a plurality of models are combined through a Stacking voting integration method, and the advantage of each model is utilized to prevent a single model from falling into a local optimal solution. According to the method, advantages and characteristics of different models are effectively integrated, and the overall performance and robustness of an identification system are remarkably improved. According to the method, the fraud identification accuracy is improved, and the calculation cost and the resource consumption are remarkably reduced.

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 computers, and discloses an Excel import and export component system based on modular design, comprising the following modules: a field mapping module for automatically performing field mapping and generating a field mapping relationship according to semantic similarity between fields of a source system and a target system; the invention further provides an Excel import and export method based on modular design. The method comprises the following steps that a source data file is uploaded, file content is analyzed, a source field is recognized, and field mapping and data processing are prepared; a mapping relation between a source field and a target field is automatically generated through a field mapping module, and the mapping relation is optimized under the support of an optimization module. According to the method, the whole data processing process is divided into five independent modules including field mapping, data type conversion, data cleaning and anomaly detection, optimization and user interface, so that the efficient and automatic data processing effect is achieved, and the problems of performance bottleneck and non-extensibility when a traditional system faces complex tasks are solved.

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 belongs to the technical field of IT type project cost financial management, and discloses an IT type project cost financial independent accounting system, which comprises a project management module, a receivable management module, a payable management module, a purchase management module, a financial system data exchange module, a human resource data exchange module and an early warning management module. According to the system, integrated management is adopted, project cost is monitored in real time and dynamically adjusted, the system collects and updates cost data in real time, rapid adjustment is carried out once deviation is found, it is ensured that the cost is controlled within a prediction range, project management flexibility and response speed are improved, cost hyper-branched risks are reduced, and meanwhile through automatic data processing and accounting processes, the project management efficiency is improved. The cost accounting accuracy and efficiency are remarkably improved, personal errors are avoided, manual calculation is simplified, a project manager can efficiently master the cost condition, powerful data support is provided for project decision making, and the scientificity and effectiveness of project management are ensured.

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 invention relates to the technical field of carbon transaction, and discloses an application method of AI aid decision in carbon transaction and carbon integrated management, comprising the following steps: S1, data collection: collecting carbon emission data of an enterprise in real time through an intelligent sensor, an Internet of Things platform and a third-party data source; s2, intelligent analysis: analyzing the collected data by using a machine learning algorithm, identifying the carbon emission trend, predicting the carbon emission in the future, and evaluating the dynamic state of the carbon transaction market; and S3, transaction decision making: making a carbon transaction strategy through an AI algorithm based on an analysis result. According to the invention, a machine learning algorithm is used to analyze the collected data, identify the carbon emission trend, predict the future carbon emission, evaluate the dynamic state of the carbon trading market, draw a situation map according to the data, sense the future trend, provide suggestions, and provide potential trading risks and solution suggestions. Automatic data processing and transaction decision-making reduce manual operation and improve work efficiency.

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 present application discloses a data processing method, device and medium based on a KETTLE script generation tool, aiming to solve the problems of low data acquisition efficiency and weakened data timeliness in the prior art where human labor is used to generate acquisition scripts for data processing. The method includes: determining the data requirements corresponding to the data requester, writing a data dictionary corresponding to the data requirements, and determining the database information corresponding to the data requirements; inputting the fields to be collected in the data dictionary and the corresponding database information into the KETTLE script generation tool, and generating a corresponding data acquisition script based on the KETTLE script generation tool; verifying the data acquisition script through the KETTLE script generation tool, and in the case of verification errors, adjusting the data acquisition script to obtain a data acquisition script that passes the verification; performing data acquisition based on the data acquisition script that passes the verification, and verifying and correcting the collected data to achieve automated data processing.

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.

The present invention relates to the field of data processing, and particularly to a method and device for automatic data processing and display based on an ERP system, which includes: obtaining source data in real time and extracting target data from the source data; determining whether the target data meets the configured conditions, and when the target data meets the configured conditions, classifying the attributes of the target data according to the attribute criteria to obtain real-time data subsets for each attribute; obtaining the historical total data subsets for each attribute, constructing a verification model based on the historical total data subsets, and inputting the real-time data subsets for each attribute into the corresponding verification models respectively, and analyzing whether there are errors in the real-time data subsets of each classified attribute through the corresponding verification models; when the verification models analyze that there are no errors in the real-time data subsets of each classified attribute, fusing the real-time data subsets of each classified attribute with the historical total data subsets of the corresponding classified attributes according to the statistical period; and displaying the statistical data based on the updated statistical data.

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.