208 results about "Analysis working" patented technology

The invention discloses a dialogue type data analysis method and device, a storage medium and electronic equipment, and relates to the technical field of data analysis. The method comprises the steps that a natural language text input by a user is acquired; obtaining corresponding semantic pre-analysis information based on the natural language text; matching a corresponding mode mapper based on the semantic pre-analysis information; obtaining corresponding semantic information based on a mode mapper; converting the semantic information into corresponding semantic information conversion parameters; analyzing the semantic information conversion parameter to obtain an index value corresponding to the to-be-queried index; performing anomaly detection on the index value corresponding to the to-be-queried index; and performing analysis result display on the index value corresponding to the to-be-queried index passing the anomaly detection. According to the method, information arrangement and information analysis are carried out on the natural language text input by the user, the intention of the user is known, the index needing to be queried by the user is fed back, the operation complexity is reduced, the interactivity and the real-time performance are improved, and convenience is provided for data analysis work.

The invention discloses an oil pipeline quality monitoring and evaluating method and system based on data processing, and belongs to the technical field of data processing.The method comprises the steps that sensor information is obtained, and the sensor information comprises vision, sound, temperature and vibration data; acquiring application scene information; selecting a fusion mode in combination with application scene information through early fusion, middle fusion and late fusion strategies; computing and storage resources are deployed at edge nodes close to a data source by using an edge computing method, and the edge nodes are responsible for preliminary data processing and analysis work to reduce data transmission delay; analyzing sensor information by using deep learning and machine learning algorithms, and identifying an abnormal mode and a potential fault; edge computing and cloud computing are combined to form a cloud-edge collaborative architecture, and the cloud-edge collaborative architecture is used for carrying out complex data processing and model training work. The method has the effects of reducing data transmission delay and improving the real-time performance of oil pipeline quality monitoring.

A modular open system architecture for common intelligence picture generation is disclosed. The system receives intelligence requirements through a multimodal artificial intelligence system and calculates collection feasibility across multiple intelligence sources based on physical and temporal conditions. The system develops integrated collection plans through the containerized analytics workbench using containerized analytics modules and processes intelligence through GPU-accelerated deep learning models for automated target recognition. Satellite collection is orchestrated through satellite data acquisition optimization platform by evaluating weather conditions, orbital parameters, and sensor capabilities, while space domain awareness is maintained through space domain awareness system for real-time collection asset management. Multi-source intelligence data is fused through multi-source intelligence fusion system to populate a common intelligence picture. The system implements automated workflows for intelligence analysis and dissemination while maintaining security controls, with the containerized analytics workbench providing pattern of life analysis and dynamic exploitation through containerized microservices.

The invention provides a planning analysis workflow intelligent arrangement method and device based on a natural language instruction, and the method and device can deeply understand the complex analysis intention of a plan in a natural language through a mixed analysis engine comprising a large-scale language model and a named entity recognition model. And according to the understood intention, a proper operator and a proper model are autonomously selected from a tool library in combination with a planning analysis knowledge graph, so that a complete, logic self-consistent and executable multi-step analysis workflow can be autonomously and dynamically arranged, the workflow is automatically executed, and multi-modal data is collected. According to the method and the device, the technical problems in multiple aspects from keyword matching to composite intention deep understanding, from artificial process design to knowledge-driven intelligent arrangement and from one-way instruction execution to interactive exploration analysis in the prior art are solved, and the method and the device have the advantages that the technical problems in multiple aspects from keyword matching to composite intention deep understanding, from artificial process design to knowledge-driven intelligent arrangement and from one-way instruction execution to interactive exploration analysis are solved; the planning work efficiency can be improved, the technical threshold is reduced, and industry digital transformation is promoted.

The invention provides an audit data analysis method based on a large language model. The audit data analysis method comprises the following steps: analyzing a natural language request: judging whether the request is structured data or unstructured data; multi-modal result fusion: an audit data analysis system of the large language model comprises an intelligent analysis module, an SQL assistant module, a document assistant module and a general intelligent module, and data streams among the modules are transmitted through an intranet encryption channel; by constructing an intelligent data analysis system based on a large model, an integrated process of'natural language questioning-gt, automatic SQL generation-gt and data analysis results' is realized, auditing personnel are assisted to efficiently complete data analysis work, the defects in the prior art are overcome, and the method has important research significance and use value.

The invention provides a service performance anomaly detection and disposal method based on an AI agent, and belongs to the field of mobile communication. Establishing a professional knowledge base for the business themes; packaging and developing a tool set with independent functions according to business function requirements; the method comprises the following steps: constructing an AI agent by adopting a large model platform, integrating a professional knowledge base and an intelligent tool set, and arranging a business analysis processing flow of the intelligent tool set; and the AI intelligent agent can automatically execute a business analysis processing flow, carry out anomaly detection and analysis processing on business performance, and output a comprehensive analysis conclusion. Automation of the disposal process is achieved through the AI agent, manual analysis is replaced, the working difficulty of complaint analysis of a user is lowered, the usability of a complaint analysis tool is improved, and the efficiency and accuracy of complaint analysis processing are improved.

The invention discloses a flow resistance and heat transfer simulation analysis method for a thermal management refrigerant side integrated module, and relates to the technical field of computer simulation. The method mainly comprises the following steps of: dividing a computational domain model into a solid domain, a fluid domain comprising a plurality of single-phase flow channel sub-domains and a flow channel section which is in a gas-liquid two-phase state and exchanges latent heat along with phase change in combination with the need of an actual analysis working condition; performing polynomial fitting on various parameters by fixing the inlet pressure value of each single-phase flow channel sub-domain; loading the fitted physical property function to the corresponding runner sub-domain, and setting a constant material attribute for the solid domain runner plate; a conjugate heat transfer model is started on an interface of a fluid domain and a solid domain, and interface heat flux density conservation and temperature continuity simulation is carried out; setting boundary conditions; and executing conjugate heat transfer simulation calculation until convergence calculation is completed. According to the method, the simulation precision is improved through fusion of three core technologies of dynamic change physical property fitting, solid-liquid conjugate heat transfer coupling and two-phase flow latent heat equivalent modeling.

The invention relates to a scenic spot passenger flow analysis system and a distribution method thereof, and belongs to the technical field of scenic spot management. The scenic spot passenger flow analysis system comprises a data collection module, a data cleaning module, a model construction module, a data statistics module and a data visualization module; the data collection module comprises network platform reservation system data, ticket checking system data and camera monitoring system data. The scenic spot passenger flow analysis system and the distribution method thereof are suitable for existing hot scenic spot passenger flow analysis work, the number of tourists can be simply recorded, and passenger flow data analysis can be carried out on tourist behaviors, preferences and activity rules; therefore, a reference can be provided for market promotion, an improvement direction can be provided for promotion of products and promotion services in scenic spots, managers are assisted in shunting tourist routes, and a scenic spot guide system is optimized.

Embodiments facilitate software analysis by machine learning (ML) models, through extensible software analysis architecture (ESAA) or software analysis work allocation (SAWA). Pluggable ESAA ML modules include a vetted prompt which is actionable for software analysis, with a vetting certification. Some ML modules contain computational cost information such as a token count or model round trip time. Tools are tailored to ML analyzers to control background execution, availability offerings, and results displays. SAWA determines how well a software analyzer meets a prompt's software analysis requirements, and an ML planning model generates an analysis plan that balances software analysis workloads among ML analyzers and non-ML analyzers. ML analyzers are favored for summarization, task decomposition, task scheduling, and source code change review, while non-ML analyzers are otherwise favored. Non-ML analyzers gather control flow, data flow, internal structure, and similar context which is then supplied to an ML analyzer.

The invention provides a tire contour digital holographic image scanning analysis working method and system and a medium, and the method comprises the steps: S1, starting scanning equipment, scanning an outer side tread, and then scanning a tire inner ring of an inner ring; s2, importing scanned tire data into a holographic size generation model, and executing a scanned file importing instruction to form a readable model file; s3, aligning the tire contour data, and selecting an optimal fitting measurement object to perform modulus fitting operation; s4, measuring features are selected through the list directory tree, input feature options in the menu bar are executed, a deviation vector instruction is executed, and therefore errors are adjusted; and S5, executing a report table creating instruction, selecting a feature position needing to be displayed, and generating a digital holographic image containing data of the tire contour size through a display terminal.

The invention relates to a new energy simulation model management method and device, electronic equipment and a storage medium, and relates to the technical field of power system digital simulation, and the method comprises the steps: constructing an element model library, an equipment model library and an algorithm model library; according to the electrical information and modeling precision requirements of the new energy station, indexing the element model library, the equipment model library and the algorithm model library, and constructing a new energy station model library; according to the new energy base electrical information and modeling precision requirements, indexing the element model library, the equipment model library and the new energy station model library, and constructing a new energy base model library; and formulating naming and query calling rules for the different levels of model libraries. Therefore, unified modeling management can be carried out on the new energy station project, repeated information collection and basic element modeling and analysis work are reduced, and the management and calling efficiency is improved.

The invention discloses a full-process high-throughput metallographic specimen preparation platform and method. The platform comprises a chuck storage unit, a full-automatic grinding and polishing unit, a corrosion drying and conveying unit and an operation control unit. According to the platform, a plurality of units are integrated together, sample chucks are conveyed through the truss and the truss manipulator on one conveying unit, and two clamping jaws are arranged at the lower end of the truss manipulator, so that a plurality of samples can be machined on the working platform at the same time, and assembly line operation is achieved. According to the metallographic full-process preparation technology, grinding, polishing and etching treatment can be carried out on a batch of metallographic samples, and the preparation efficiency of the metallographic samples is greatly improved. In the preparation process, only in the sample clamping work and the equipment operation work process, operation of testers is needed. Other processes do not need manual intervention, so that the labor intensity is reduced. The polishing sample which is free of any scratches and is in a mirror surface state can be prepared in batches, and a powerful sample preparation basis is provided for follow-up metallographic analysis work.

The invention discloses a firmware vulnerability detection method based on differential symbolic execution, and belongs to the technical field of vulnerability detection. The method comprises the following steps: acquiring firmware images of different configurations of the same equipment, acquiring firmware images in an image set, extracting executable binary files from the firmware images of different version numbers by using a firmware extraction tool, positioning changed code snippets in the binary files, filtering difference points irrelevant to a target vulnerability type, generating a difference list, and storing the difference list in a database; the difference points in the difference list are mapped into a symbolic execution engine, the marked difference points are subjected to priority ranking, a priority ranking set is established, a binary analysis test model is established, the difference points in the priority ranking set are obtained, differentiation analysis is carried out, and a differentiation analysis result is obtained; locating vulnerabilities according to the differentiation analysis result to generate a vulnerability report. According to the method, potential vulnerabilities and security problems can be found more quickly and accurately, unnecessary analysis work is reduced, and powerful support is provided for security protection of equipment.

The invention provides a creative video understanding and analyzing system and a creative video understanding and analyzing method, which relate to the technical field of image video processing and adopt a collaborative architecture formed by sequentially connecting intelligent agents in five stages of video sub-mirror identification, video outline extraction, creative factor analysis, shooting logic induction and audio rhythm analysis in series. The full-process end-to-end automatic analysis and generation of the creative videos from original input to structured creative video scripts are realized, and through professional division and collaboration of multiple agents, deep mirror segmentation, plot logic carding, creative bright spot extraction, shooting technique induction and sound and picture rhythm matching of the videos can be automatically completed; according to the method, manual analysis work which needs multi-field experts to consume several hours and even several days originally is compressed to be completed in minutes, the creative video generation efficiency is improved, the professionality and consistency of output results in the aspects of mirror splitting, narration, vision and audio are guaranteed, and the manpower and time cost of advertisement creative analysis and script generation is reduced.

The invention discloses an automatic and high-flux integrated device for sample detection pretreatment of a gas chromatograph, and relates to the technical field of detection equipment, the automatic and high-flux integrated device comprises a gas chromatograph main body and a shell, one end of the gas chromatograph main body is fixedly connected with the shell, the top end of the shell is fixedly connected with a placing rack, a weighing mechanism and an extraction mechanism, and the placing rack is fixedly connected with the gas chromatograph main body. One end of the extraction mechanism is communicated with a liquid separation mechanism, a liquid outlet is formed in the inner side of the shell, one end of the shell is rotatably connected with a second door plate, and a waste liquid box is placed on the inner side of the shell. After sample treatment is completed, the device can automatically execute a cleaning procedure without manual intervention, and due to the high-automation design, the automation level of the device is remarkably improved, the overall detection efficiency is greatly improved, and powerful support is provided for experimental analysis work.

According to the product reliability analysis method and device, the electronic equipment and the storage medium, the functional parts of the product are decomposed according to the working stages, clear functional module division is formed, and the analysis precision is ensured. Through identification and combination of working state units of all the function modules, basic function units are constructed, and internal logic of product functions is further revealed. On the basis, the function transmission relation between basic function units is determined, a function implementation model of the product is constructed, an effective basis is provided for reliability simulation analysis, the effectiveness of reliability analysis work is ensured, reliability is considered in the product function design stage, and the reliability analysis efficiency is improved. The effectiveness of reliable work is guaranteed, potential quality risks can be effectively avoided, and the product quality is ensured.

The invention provides a closed-loop analysis optimization method for an acoustic subsurface buoy system, and belongs to the technical field of marine monitoring system optimization. According to the method, a mode of combining overall static force calculation, VIV characteristic calculation, local CFI calculation and FW-H acoustic ratio simulation calculation is provided, and analysis on the influence of the VIV characteristics of the subsurface buoy system, the self noise of the hydrophone and the noise of other hydrophones is achieved; according to the method, the problem that CFI numerical simulation cannot be directly carried out on the whole is solved, and static characteristic and whole VIV characteristic calculation is carried out on the system so as to carry out local CFI numerical simulation and FW-H acoustic ratio simulation calculation; the whole calculation process can be circularly optimized for multiple times. According to the method, the analysis work of each part is considered as a whole, an organic overall closed-loop system is formed, multiple times of cyclic optimization can be carried out according to the index requirements of the subsurface buoy system, and the optimal design of the acoustic subsurface buoy system is achieved.

The invention belongs to the technical field of digital diagnosis, and discloses an enterprise digital diagnosis platform and a use method thereof, and the platform comprises a diagnosis management user unit which is used for carrying out the comprehensive management of a management user based on the enterprise diagnosis information; the enterprise user diagnosis unit is used for analyzing the diagnosis task of the enterprise user and providing diagnosis service and personalized support for the enterprise user according to the diagnosis task; the business authority management unit is used for defining the function access range of the enterprise user and the management user, and performing unified management on the function authority of the enterprise user and the management user based on the function access range; and the user role management unit is used for constructing a diagnosis management role and a diagnosis enterprise role. The method focuses on maintenance of global data, distribution of diagnosis tasks and comprehensive analysis, so that efficient organization and coordination of platform resources are facilitated, and stable operation of the platform and smooth development of enterprise diagnosis work are ensured.

The utility model relates to the technical field of cold box interlayer gas oxygen content analysis, in particular to a cold box interlayer gas oxygen content on-line analysis device which comprises a sampling pump, a three-way electromagnetic valve, a pretreatment box, an analysis instrument and a control system, wherein the sampling pump is used for pressurizing and introducing interlayer gas of the cold box into the analysis device; the analysis instrument is used for analyzing the oxygen content in the pretreated gas; the three-way electromagnetic valve is arranged between the sampling pump and the analysis instrument and is used for remotely switching and analyzing the waste nitrogen and the cold box interlayer gas; the pretreatment box is connected between the three-way electromagnetic valve and the sampling pump. Through remote switching of the three-way solenoid valve and automatic logic setting of the DCS, online intelligent analysis of the oxygen content of the interlayer gas of the cold box is achieved, and the analysis accuracy and efficiency are improved; and an operator can finish the analysis work of the waste nitrogen and the interlayer gas of the cold box without frequently and manually switching an analysis instrument, so that the operation burden is reduced.

The invention discloses an energy data classification and grading method, system, equipment and medium based on a BERT model, and relates to the technical field of power system data grading and classification, and the method comprises the specific steps: making a data classification and grading rule, collecting a data set, carrying out the preprocessing of the data set, constructing an energy data classification and grading model, and carrying out the classification and grading of the energy data according to the data characteristics of the energy industry; and inputting the preprocessed data set, evaluating and optimizing the model, and executing an energy data classification and grading task according to the model. The method does not need to depend on traditional manual rules or tedious feature engineering, and is suitable for classification and grading scenes of massive and multi-type energy data of an energy big data center. The method has the advantages of being high in energy data classification and grading efficiency, high in recognition precision, adaptive to energy industry data characteristics and low in operation and maintenance cost, and can effectively support subsequent data processing and analysis work of an energy data center.

The present invention discloses a method, system, and device for mouse event interaction based on a general gyroscope, belonging to the technical field of mouse event interaction. The method includes the following steps: monitoring the output data of the gyroscope in a stationary state, and processing the output data of the gyroscope in a stationary state to obtain an evaluation value of the static offset degree of the gyroscope; collecting the output data of the gyroscope, and performing initial data calibration on the output data of the gyroscope according to the evaluation value of the static offset degree of the gyroscope; monitoring the working environment data and the working state data of the gyroscope, comprehensively analyzing the working environment data, the working state data, and the evaluation value of the static offset degree of the gyroscope to obtain an evaluation value of the dynamic offset degree of the gyroscope.

The invention belongs to the technical field of data mining, and particularly provides a group mining method and system based on video image trajectory analysis, and the method comprises the steps: obtaining a multi-dimensional attribute data set of a plurality of attention targets; focusing targets in the multi-dimensional attribute data set are defined as nodes, two nodes passing through the same attribute case are connected through edges, the edges connected end to end form a path, and a graph is obtained; a depth-first search algorithm is adopted to search the graph, a sub-graph is obtained through recognition, and any two nodes in the sub-graph are connected through a path; for each sub-graph, a Louvain algorithm is adopted to carry out more detailed community division, a group graph is obtained, and any two nodes in the group graph are in edge connection. The method is suitable for processing a large-scale and complex network structure, and can provide an accurate specific group structure mining result while ensuring high efficiency. The system can quickly screen out important data and deeply analyze the important data, so that identification and analysis work of a specific group is effectively supported.

The invention discloses a log parameter semantic analysis method and device and a storage medium. The method comprises the steps of obtaining initial log data; extracting a target log parameter in the initial log data, and determining a target clustering template corresponding to the target log parameter; determining N candidate tags corresponding to the target log parameter according to the initial log data, the target clustering template and a first preset large language model; based on the N candidate tags, determining the similarity between the target log parameter and m-1 log parameters to obtain m-1 tag similarities; and determining a target tag according to the target clustering template, the N candidate tags, the m-1 tag similarities, the m-1 log parameters and a second preset large language model. By adopting the embodiment of the invention, the efficiency of log analysis work is improved.

The utility model relates to the technical field of liquid medicine analysis, and discloses a full-automatic line body liquid medicine analysis system which comprises a supporting foot device, a fixing rod is fixedly connected to the top of the supporting foot device, a color recognizer is fixedly connected to the outer wall of the fixing rod, a sliding block is connected to the outer wall of the fixing rod in a sleeved mode, a screw rod fixator is connected to the inner wall of the sliding block in a sleeved mode, and the screw rod fixator is connected with a screw rod. According to the full-automatic line body liquid medicine analysis system, through mutual cooperative use of the experiment cup, the burette and the color identifier on the device, after pure water, a bromophenol blue indicator and a titrating solution are added into an inner cavity of the experiment cup on the device, the titrating solution is added into the inner cavity of the experiment cup, so that the titrating solution is separated from the inner cavity of the experiment cup, and the titrating solution is separated from the inner cavity of the experiment cup; the color recognizer is used for automatically detecting the color change in the inner cavity of the experiment cup, and the pump body connected with the other side of the burette is used for transmitting data to the system, so that the system automatically calculates the concentration of Na2CO3, and the liquid medicine analysis work is completed.

The invention discloses a rock core CT image crack segmentation method and device based on deep learning. The method comprises the following steps: making a training data set; expanding the number of training samples in the training data set to form a new data set; a deep learning network model is constructed, the deep learning network model comprises a U-Net network, a contraction path for feature extraction in the U-Net network adopts a feature extraction network based on a VGG-16 network, and an up-sampling expansion path in the U-Net network is added with a CBMA attention module. The CBMA attention module is used for changing the attention of the model to different spatial positions and different channels in the feature map and improving the weight of the area where the rock core crack is located; performing training and parameter adjustment on the deep learning network model by using the training set until the model converges; and testing the trained deep learning network model by using the test set, and evaluating the crack segmentation effect of the deep learning network model. According to the invention, the efficiency of rock core CT image automatic analysis work can be improved.

The invention discloses an intelligent fault tree generation method based on cooperation of a multi-modal large model and a large language model, and relates to the field of fault tree analysis. In order to solve the defects of low tree building efficiency, insufficient cross-modal information processing and incomplete fault causal chain reasoning in the prior art, the technical scheme provided by the invention comprises the following steps: carrying out topological structure analysis on a system flow chart by adopting a multi-modal large model to obtain an equipment network table; taking the equipment network list as input, and performing fault mode directional retrieval on the equipment information base by adopting a large language model to obtain a fault mode list; taking the equipment network list and the fault mode list as input, performing failure reason reasoning by adopting a large language model, and establishing a fault causal chain from a system layer to an equipment layer; and taking the fault causal chain as input, constructing a fault tree by adopting a large language model, and generating a complete fault tree structure from a system top event to an equipment basic event. The method is suitable for safety and reliability analysis work of a complex industrial system.

The invention discloses a small-deformation contact nonlinear simulation method, which belongs to the technical field of contact nonlinear simulation, and comprises the following steps: S1, carrying out contact simulation at a contact interface by adopting a friction spring; s2, setting a nonlinear analysis working condition in finite element analysis software; and S3, performing small deformation contact nonlinear simulation and calculation on the structure. According to the small-deformation contact nonlinear simulation method, important references are provided for accurate calculation and design, material saving, energy consumption reduction, production efficiency improvement and the like of structures such as modular units and beams, laying of tunnel linings and the like, the application mode of the small-deformation contact nonlinear simulation method can be embedded into a program to form automatic options, and digital twinning is achieved.

The invention relates to the technical field of petrochemical engineering analysis, and provides a form analysis method and system for sulfides in a sulfuric acid alkylation working solution, and the analysis method comprises the following steps: S1, sample collection and pretreatment; s2, carrying out derivatization reaction; s3, separating and detecting; s4, data processing and analysis; the system comprises a sample pretreatment module, a derivatization reaction module, a separation detection module and a data processing and analysis module, and the analysis method provided by the invention can accurately and quickly analyze the forms and contents of various sulfides in the working solution, is high in sensitivity and accuracy, simple, convenient and quick to operate, has good universality and expansibility, and can be widely applied to industrial production. The method is suitable for qualitative and quantitative analysis of various sulfide forms in the field of petrochemical engineering, and has important industrial application value.

The technical scheme of the present application discloses a kidney transplantation single disease follow-up database system based on a hospital intranet environment, comprising a data integration layer, an intelligent analysis layer and a doctor-patient linkage layer. Through the cooperative operation of the three-layer technical architecture designed by the present application, the three core problems of the prior art are comprehensively solved, and the following technical effects are achieved: at the data integration level, automatic and real-time integration of multi-port medical data of kidney transplantation patients is realized, the data integration efficiency is improved by 90%, the accuracy rate reaches 99.5%, and the traceability and privacy security are significantly improved; at the data analysis level, the AI-driven analysis model realizes automatic generation of patient whole-cycle health reports, large-sample group feature mining and real-time abnormality early warning, and the doctor data analysis workload is reduced by 80%, and the abnormal data response time is shortened to the minute level.

Examples include bypassing a portion of an analytics workflow. In some examples, execution of an analytics workflow may be monitored upon receipt of a raw data and the execution may be interrupted at an optimal bypass stage to obtain insights data from the raw data. A similarity analysis may be performed to compare the insights data to a stored insights data in an insights data repository. Based, at least in part, on a determination of similarity, a bypass operation may be performed to bypass a remainder of the analytics workflow.