124 results about "Automatic Data Processing" patented technology

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 discloses a user abnormal behavior monitoring method and device, equipment, a medium and a product. Relates to the technical field of deep learning, network security and financial science and technology, and comprises the following steps: obtaining logs generated by a user within a set time, dividing and clustering according to a target time period to obtain a clustering log set, analyzing the clustering log set to obtain a corresponding behavior event label set, and combining and inputting the two into a pre-trained long and short-term memory model to obtain a behavior event label set; and obtaining at least one target behavior operation predicted for each piece of target mark data and a corresponding target behavior occurrence probability, and carrying out abnormal behavior monitoring on the target user according to a matched abnormal monitoring rule based on the target behavior operation and the occurrence probability thereof. Through fusion of the deep learning model and clustering analysis, the monitoring accuracy is improved, the manpower and time cost is reduced through an automatic data processing mode, the monitoring efficiency and the real-time performance are improved, and thus the reliability of user abnormal behavior recognition and safety evaluation is improved.

The invention relates to the technical field of human resource management and information, and discloses an employment post recommendation method based on a human resource database, and the method comprises the following steps: S1, data collection; s2, data processing; s3, keyword extraction; s4, performing similarity calculation; s5, post filtering and sorting; s6, post recommendation; and S7, effect evaluation: through automatic data processing and similarity calculation, resumes most matched with post demands can be quickly screened out, the workload of recruiters is reduced, accurate matching degree evaluation is beneficial to realizing optimal configuration of talents and posts, employee loss and recruitment cost waste caused by mismatching are reduced, and the efficiency of recruitment is improved. The recruitment will and the matching degree of the job seekers can be improved through accurate recommendation, so that the recruitment success rate and efficiency are improved, more high-quality job seekers are attracted through efficient post recommendation and accurate matching, and the talent reserve and competitiveness of enterprises are enhanced.

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 invention relates to the technical field of artificial intelligence and the field of financial science and technology, and discloses a business report generation method, which comprises the following steps: acquiring business data, inputting the business data into a text generation model, and generating a plurality of business description texts; inputting the business data into an image generation model to generate a plurality of business display images; performing association matching on the service description text and the service display image to obtain a text and an image which are associated with each other; and integrating the mutually associated text and image to generate a complete report. According to the method, the text generation model and the image generation model are combined, and the generated text and image are intelligently matched and integrated, so that the content richness and readability of the report are improved. Meanwhile, through automatic data processing and generation steps, the generation efficiency is improved, and the accuracy and consistency of data description and image display in the report can be ensured.

The invention discloses a clinical test quality evaluation method and system based on artificial intelligence, and relates to the technical field of clinical test quality evaluation. Through a series of automatic data processing and model evaluation processes, automatic operation is basically realized from data acquisition to final report generation, manual complex evaluation calculation on a large amount of data is not needed, and the evaluation efficiency is greatly improved; evaluation is carried out through an artificial intelligence algorithm and a rule-based expert system, so that the influence of subjective factors on an evaluation result is effectively reduced, and the consistency and accuracy of the evaluation result are improved; according to the method, multiple types of high-dimensional data are processed through an artificial intelligence algorithm, key feature subsets are extracted through feature extraction and screening, a trained deep learning model is used for evaluation, the method adapts to constantly changing large-scale and high-dimensional data conditions by constantly optimizing model performance, and the requirement for efficient and accurate evaluation is effectively met.

The invention discloses a spring probe system for rapid registration of articular cartilage based on 3D printing, and relates to the technical field of medical imaging and orthopedic surgery navigation. The problem that the joint registration precision is insufficient due to the fact that cartilage cannot be developed in traditional CT imaging is solved. Through personalized customization of the 3D printing guide plate, convenient installation of positioning holes, adjustability of the spring probe assembly and real-time data monitoring, and automatic data processing of the intelligent registration module, manual operation is reduced, the operation efficiency is improved, the spring probe assembly is reasonable in structure and adjustable in elastic force, stable operation of the system in an operation is guaranteed, and the operation safety is improved. Multi-position CT scanning is combined with an advanced image processing and registration technology, an accurate initial model is constructed, a spring probe assembly collects data and is combined with an elastic deformation compensation model to correct registration errors in real time, the registration accuracy is improved, reliable support is provided for orthopedic surgery navigation, the surgery success rate can be improved, and patient wounds and surgery risks are reduced.

The invention discloses an automatic construction system for financial data management, and relates to the related technical field of financial data management, and the system comprises a user interface module which is used for providing an intuitive graphical interface, and enabling a user to construct an application process in a mode of dragging a component; the business logic module is used for calculating the production cost of the product and automatically generating an asset balance sheet, a profit sheet and a cash flow sheet; and the financial trend prediction module needs historical financial data as input, the user inputs financial data and related characteristics, and the model outputs a prediction result. An automatic data processing and report generating system can be rapidly constructed through an automatic tool, the labor burden is relieved, a low-code platform system allows a user to customize and adjust the financial process in a visual mode, the individual requirement can be met without compiling a large number of codes, and the user experience is improved. The LLM technology can provide natural language understanding and intelligent analysis ability, and assists non-professionals in deep financial insight and strategic decision making.

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 present invention discloses a method for generating a rotor fault diagnosis model based on multiple transform domains and a diagnosis method. The former includes: collecting vibration signal data of a modular rotor fault of a gas turbine in multiple categories to construct a training and test data set; transforming each data to the short-time Fourier time-frequency domain using the STFT transform domain, transforming it to the Morlet wavelet time-frequency domain using the Morlet wavelet transform domain, and transforming it to the complex network phase space domain using the complex network recurrence plot method; inputting the training data set transformed by the three transform domains into a preset model, and using the CNN network layer for feature extraction; using the LSTM network to perform feature structure learning on the output features, and training to obtain a rotor fault model; using the test data set transformed by the three transform domains to verify and adjust the rotor fault model to obtain a rotor fault diagnosis model for fault detection. The present invention can realize automatic data processing, reduce manual input, and improve the efficiency and accuracy of fault diagnosis.

The invention relates to the field of optical fiber sound wave sensing and positioning, in particular to an optical cable rapid positioning system and a method thereof, the positioning system does not depend on real-time network communication, can stably operate even in an environment without a communication network, shows obvious advantages, and can realize rapid positioning by playing characteristic sound waves with specified frequency components. The interference of environmental noise can be effectively reduced, the positioning accuracy can be remarkably improved, even in a noisy environment, the accuracy of a positioning result can be ensured by applying a high-strength characteristic signal and filtering noise interference of a non-target frequency band, and the accuracy of a positioning result can be ensured by adopting an offline acquisition-online processing mixed framework. The environmental adaptability and the automatic data processing capability of the system are obviously improved, and the complexity and the potential error rate of manual operation are greatly reduced; the problems that an existing optical cable positioning system and method depends on GPS positioning and a real-time communication network and is easily influenced by subjective judgment, the calculation efficiency of all-point analysis is low, and the number of participants is too large are solved.

The invention discloses an online car-hailing driver fatigue driving pre-judgment method and system. The invention relates to the technical field of online car hailing. And collecting driver departure data O and driver order receiving data M which are arranged according to a time sequence. O = [O1, O2,..., ON]; m = [M1, M2,..., MN]; o1, O2,..., ON and M1, M2,..., MN are historical data of driver departure data O and driver order receiving data M respectively. Executing exponential smoothing according to the trend and the seasonality of the driver departure data O and the driver order receiving data M in the time sequence; by adopting the Holt-Wittes seasonal model, the method can accurately capture the periodicity and tendency characteristics of the driving and order receiving behaviors of the driver, and significantly improves the prediction accuracy. The automatic data processing and prediction process greatly shortens the prediction period, improves the operation efficiency, and enables the platform to respond to the potential risk of fatigue driving of the driver more quickly.

The utility model relates to the technical field of testing devices, and discloses a paper diaper permeability tester which comprises a tester body, a first lifting device and a second lifting device which are arranged on the same horizontal line are arranged at the top of the inner side of the tester body, and a translation device is arranged at the corresponding position of the bottom of the tester body; a liquid adding module is arranged on the first lifting device, a pressurizing module is arranged on the second lifting device, and a sample holder is arranged on the moving device; the liquid adding module is connected with a liquid adding device, the liquid adding device comprises a water pipe, and the liquid adding device is connected with the liquid adding module through the water pipe. The tester is simple in structure, suitable for batch production in factories, high in automation degree, accurate in testing and capable of automatically processing data and effectively saving labor cost.

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.

The invention relates to the technical field of automatic data processing of computer software, in particular to a data interaction method based on a browser plug-in, which comprises the following steps: acquiring a starting instruction of a user, and starting the plug-in according to the starting instruction; the plug-in obtains an element of a target page selected by a user, and captures a unique identifier of the element; and the plug-in executes automatic data interaction based on the element according to a condition configured by a user. According to the technical scheme provided by the invention, complicated IT support and hardware configuration are not needed, and the unique identifier of the target page element is captured, so that the accuracy and consistency of subsequent element-based operation execution are ensured; the local encrypted and stored operation record ensures the security of the sensitive data, prevents data leakage, is also convenient for an administrator to examine and trace the operation history, and is beneficial to application in an efficient management environment.

The invention discloses a cement stabilized macadam mesoscopic fracture parameter rapid inversion method, and the method achieves the multi-dimensional improvement of model scale selection, automatic data processing, machine learning model construction, parameter result optimization and the like through the construction of an inversion process of a discrete element model-XGBoost model-particle swarm optimization model frame. The inversion efficiency is improved; the time and energy consumed by repeated manual trial calculation are reduced; the multi-objective optimization advantage of a vectorization particle swarm optimization algorithm is fully utilized, and the vectorization particle swarm optimization algorithm is combined with an XGBoost model, so that the optimal solution of a target vector is realized; compared with a manual trial and error method, the method has the advantages that multi-dimensional targets can be optimized at the same time, so that a real test result is approached at the fastest efficiency, and the precision of the cement stabilized macadam microscopic fracture parameters is greatly improved.

The present invention discloses an industrial automatic control data processing system and method based on digital twin, which belongs to the field of industrial automation control technology. The present invention establishes a connection between the edge side and the cloud center through the edge side management module, automatically collects industrial data through the edge collection node, and stores the collected industrial data in the edge device; sends a data request to the cloud center through the data mapping module, and the cloud center receives the industrial data uploaded by the edge side and maps the received industrial data in the digital space based on the digital twin technology; analyzes and feedbacks the data collection status of the edge side through the cloud processing module; updates the data collection strategy of the edge side according to the analysis results fed back by the cloud center through the collaborative control module, and transmits the updated data collection strategy to the edge device, and adjusts the data collection business of the edge collection node. The data in the industrial production process is processed more flexibly, which reduces the resource consumption of operation and maintenance.

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 invention discloses a pressure test system suitable for an energy storage monitoring system and a test method thereof. The pressure test system is provided with a task management module, a data object module, a strategy control module, a communication management module, a message monitoring module and a data processing module. The system can provide powerful support for test and acceptance of an energy storage monitoring system, can process and simulate a large number of energy storage devices, provides a test platform capable of simulating operation of a large-scale energy storage system, supports various communication protocols and protocols, ensures interoperability of testing different types of energy storage devices and systems, and improves test efficiency. Communication of multiple channels and concurrent testing of multiple testing tasks can be simulated, automatic data processing is introduced, the testing efficiency can be greatly improved, manual intervention is reduced, human errors are avoided, and repeatability and accuracy of testing results are ensured. In addition, the test result is automatically analyzed according to the preset judgment logic, problems and abnormities can be rapidly recognized, and therefore fault diagnosis and problem solving are accelerated.

The invention provides a method for rapidly solving a plane segmentation via hole in a multilayer integrated circuit board. The method comprises the following steps: calculating a connection relation of all elements in the multilayer integrated circuit board, determining a vertical position of each via hole, identifying a plane layer intersected with the via hole, recording connection information, allocating a priority value to each plane layer, sorting according to the priority values, and creating a data structure QMaplt; a QPair is used as a QPair; int, int, and intgt; , QSett, QSett; a Viagt; gt; the data structure is converted into QMaplt; via, QSetlt, Via, QSetlt; a QPair is used as a QPair; int, int, and intgt; gt; gt; and on the basis of the obtained relation that each via hole is cut by the plane, cutting holes segmented by the plane. According to the method, through an automatic data processing and optimization algorithm, the accuracy and efficiency of via hole segmentation are improved, the design and manufacturing cost is reduced, the production cycle is shortened, and powerful technical support is provided for design and manufacturing of a multilayer integrated circuit board.

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 invention relates to the technical field of big data auxiliary decision-making systems, and discloses a natural resource big data auxiliary decision-making system based on a virtual geographic environment. According to the method, multi-level and multi-angle analysis of the natural resource big data is realized, a flexible automatic data processing mode greatly improves the working efficiency, the accuracy and authenticity of the natural resource big data analysis result are ensured, and a decision basis is provided for protecting cultivated land resources, strictly managing natural resources and strengthening the macroscopic regulation and control of national economy. According to the characteristics and types of the environmental perception data, a visualization system of the environmental perception data in a virtual geographical environment lake is provided, different visualization methods are adopted to express monitoring data of an environmental wireless sensor, and a vector field construction method is utilized to realize dynamic change of vector data in a virtual geographical environment world. Real-time environment sensing video monitoring images and virtual geographical environment scenes are fused, and real-time observation and monitoring of the birds and the water body in the Poyang Lake are achieved.

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 invention relates to the technical field of aeroengines, and discloses a method and system for diagnosing gas path faults in the starting process of an aeroengine. The method and system for diagnosing gas path faults in the starting process of an aeroengine are used to obtain a mapping relationship between an assessment parameter and a converted speed in a historical starting process, construct an envelope of the assessment parameter, and judge whether the assessment parameter at the converted speed during the test exceeds the envelope, so as to judge whether the engine starting test is a normal start. The method and system for diagnosing gas path faults in the starting process of an aeroengine of the invention can realize automatic data processing, reduce data processing time and debugging times, and provide a basis for adjusting the starter power in a speed range or optimizing the starting fuel supply law.

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.