77 results about "Change analysis" patented technology

The invention relates to the technical field of sensing data processing, and discloses an old people home safety decision service system fusing multi-mode sensing data, which comprises a data interaction analysis unit, a data change analysis unit, a data calculation unit, a safety analysis unit and a safety decision unit. The hidden association of the multi-modal indexes is accurately captured, the early degradation of the collaboration level can be perceived through the graph condensation degree and the graph equilibrium value, the collaboration degradation track can be used for analyzing the collaboration state, and the finally generated safety decision instruction can perform early warning in advance. According to the scheme, single-mode threshold dependence is broken through, hidden dangers hidden in data correlation evolution are recognized in advance, and the lagging of home safety decision of old people is solved.

The invention discloses an embedded system integration test case multiplexing method and system, and the method is characterized in that the multiplexing of a test case is carried out based on the existing software assets: firstly, based on the existing software requirements and the test case, an existing requirement-test case tracking chain is constructed; performing demand change analysis on the new demand activity graph information; performing change influence range analysis based on a change analysis result in combination with a demand-test case tracking chain, and determining a test case reuse and generation scheme; and finally, executing the test case multiplexing and generating scheme. According to the method, the tracking relation between existing requirements and test case assets is established, meanwhile, the execution cost of downstream test tasks caused by requirement change is reduced through multiplexing, and the test efficiency of integration testing is improved.

The invention relates to the technical field of automobile state monitoring, in particular to an automobile electric drive state intelligent recognition system which comprises a data acquisition module, a change analysis module, an association recognition module, a state layering module and a state recognition module. According to the method, the temperature and flow velocity dynamic states of the cooling liquid at the inlet, the outlet and the middle part of the channel are captured in real time, the time sequence characteristics reflecting the heat dissipation process of the electric drive equipment are established, the dynamic change rate of the electric power of the electric drive equipment is synchronously associated, and the linear coupling strength between the electric power input and the heat flow response output is deeply analyzed; a multi-dimensional joint feature fusing electric power change, heat flow dynamic response and response delay between the electric power change and the heat flow dynamic response is constructed, the similarity between the current operation state and various preset typical working condition features is calculated through clustering analysis, and finally affiliation judgment of the current operation state is output in a probability form. The problem of recognition fuzziness caused by complex and changeable working conditions is effectively solved.

The invention relates to a spoil field three-dimensional form change analysis method, which comprises the following steps: constructing an air-space-ground collaborative multi-scale three-dimensional monitoring network by adopting an unmanned aerial vehicle carrying a laser radar system; dynamic construction of a multi-period digital elevation model and a digital terrain model is realized through a weighted fusion algorithm based on point cloud density difference and an improved progressive triangulation network encryption algorithm; performing time sequence alignment on the digital terrain models in different periods, and constructing a digital elevation difference model; and through a digital elevation difference model and a self-adaptive threshold change detection technology, the space-time differentiation characteristics and evolution rules of a slope curvature sudden change area, a surface roughness abnormal zone and a deformation rate of the spoil site are disclosed. According to the scheme provided by the invention, high-precision three-dimensional form dynamic modeling and deformation process precise monitoring of the spoil ground can be realized, and reliable technical support is provided for ecological safety situation assessment and geological disaster advanced early warning of the spoil ground.

The invention discloses an automatic optimization system for an administrative approval process, which relates to the field of administrative approval and comprises a twin modeling module, a simulation prediction module, a scheme generation module, a feature modeling module, a dynamic routing module, a semantic analysis module, a change analysis module, a behavior intervention module, a fusion inference module and a decision support module. According to the method, a real process structure and an operation rule can be accurately copied, bottleneck nodes can be identified in different pressure scenes, intervention measures are ensured to consider efficiency, throughput and resource utilization rate, task allocation is efficient and fair by dynamically generating a routing instruction, the response speed and accuracy of approval to regulation updating are improved, and the method is suitable for popularization and application. Quantitative policy implementation effect prediction is provided for decision makers, the scheme is ensured to have transparency and auditing performance, and manual review and risk control are facilitated.

The invention relates to the technical field of medical image processing, in particular to a pulmonary nodule follow-up visit intelligent management system which comprises a pulmonary nodule intelligent matching and change analysis engine, a pulmonary nodule intelligent follow-up visit scheme generation engine, a cloud storage and collaborative service module, an early warning module and a user management and operation module. The surface of the pulmonary nodule is modeled into a differential manifold, accurate matching of the pulmonary nodule and quantitative analysis of small changes are achieved through a multi-scale differential invariant feature extraction framework and a geodesic distance-based change analysis technology, the system generates a personalized follow-up visit scheme based on a risk assessment model, and through a multi-stage early warning mechanism and multi-channel notification distribution, the risk assessment accuracy of the pulmonary nodule is improved. The system also adopts a GPU acceleration computing architecture, so that the processing efficiency is remarkably improved, multi-terminal cooperative operation is supported, the accuracy, intelligence and individuation of pulmonary nodule follow-up visit management are realized, and the follow-up visit efficiency and the early detection rate of lung cancer are improved.

The invention relates to the technical field of oral medicine and biological information analysis, in particular to an evaluation system for oral microbiological analysis and decayed tooth risk prediction. The system comprises a sample collection module, a microorganism detection module, a data preprocessing module, a microorganism population dynamic analysis module, a multi-dimensional feature extraction module, a decayed tooth risk assessment module and a personalized suggestion generation module. By constructing microbial population evolution analysis based on a Lotka-Volterra competitive model, diversity dynamic change analysis based on Shannon entropy and evolution trend prediction based on a Lyapunov stability theory, the system deeply reveals a dynamic evolution law of an oral micro-ecosystem, and a multi-dimensional feature adaptive weighting mechanism based on mutual information is adopted, so that the dynamic evolution law of the oral micro-ecosystem is improved. Personalized accurate risk assessment is realized, a causal reasoning theory is introduced to generate personalized intervention suggestions with causal support, and the accuracy and the prevention effect of dental caries risk prediction are remarkably improved.

This invention discloses a method and system for intelligent analysis of road and bridge construction data based on big data, belonging to the field of big data analysis technology. The method includes: acquiring road and bridge construction data; grouping the road and bridge construction data to obtain multiple construction data groups; performing change analysis on the construction data groups to calculate the data change rate corresponding to each type of road and bridge construction data; matching the data change rate corresponding to each type of road and bridge construction data with a micro-trend pattern template to identify change pattern combinations; and performing risk assessment on the change pattern combinations to generate early warning information, wherein the early warning information includes the affected structural parts, the change pattern combinations, and intervention measure suggestions. This invention can combine construction data grouped from different regions and pattern templates to identify change pattern combinations and generate early warning information, thereby realizing road and bridge construction data analysis and improving comprehensiveness, accuracy, and road and bridge safety.

The application discloses a kind of based on flavoromics's sun vinegar aging period flavor dynamic change analysis method, it is related to flavoromics technical field, to solve the current concentration rainstorm causes the temperature and humidity gradient of inner and outer wall of pottery jar to increase dramatically, causes the technical problem that pottery jar astringency is generated, including the following steps: S100, real-time monitoring and risk assessment of heat and humidity stress;S200, rainstorm event fusion early warning;S300, dynamic deduction and strategy optimization based on digital twinning;S400, dynamic microenvironment blocking control execution;S500, closed-loop feedback based on proxy index;S600, post-evaluation and model optimization.The application realizes early quantitative perception to astringency risk by real-time monitoring and calculating heat and humidity stress index representing ion precipitation driving force, combined with the research and judgment model of early warning confidence of fusion meteorological forecast and real-time data, starts the blocking control system, carries out physical intervention to pottery jar, guarantees the quality stability of sun vinegar in rainy season.

The invention relates to the technical field of vibration feature recognition, in particular to a method and device for recognizing the upper step or lower step vibration trend of large rotating equipment. The method comprises the following steps: acquiring monitoring data of a vibration measuring point of to-be-monitored large rotating equipment; starting from an initial data point in the monitoring data, sequentially selecting continuous data points of which the number is gradually increased to form a plurality of data subsets; for each data subset, performing linear regression fitting according to the data subset, and calculating a root-mean-square error corresponding to the data subset based on the obtained regression equation corresponding to the data subset; sequentially comparing the root-mean-square error corresponding to each data subset with a preset root-mean-square error reference value so as to identify a trend abrupt change point; and according to the monitoring data, carrying out local change analysis and front and back data segment stability analysis on the trend abrupt change point, and carrying out upper step and lower step trend identification on the monitoring data based on the obtained analysis result to obtain a trend identification result.

This invention discloses a multi-level network-type energy storage control and protection system and method, relating to the field of energy storage technology. The method includes: S1, performing feature modeling on the multi-source operating signals of the acquired energy storage system to construct a multi-source operating feature set; S2, performing time series rate of change analysis on the multi-source operating feature set to extract dynamic features of current direction change and power reversal; S3, performing energy disturbance amplitude analysis on the dynamic energy feature set to calculate an adaptive protection threshold set in real time; S4, comparing the real-time sampled signal with the adaptive protection threshold set to identify whether an over-limit state has been triggered; S5, when an over-limit state is detected to be triggered, extracting the real-time dynamic features of the over-limit event, matching the real-time dynamic features of the over-limit event with the energy backlash judgment model, determining the anomaly type of the over-limit event based on the matching result, and outputting a protection action command or dynamic balance control command corresponding to the anomaly type.

The invention discloses a training method for agent template pair training and automatic evaluation, relates to the technical field of agent training, and is used for solving the problem that the training efficiency of agent pair training is low due to the fact that behavior response characteristics and a cognitive evolution process of an agent in the actual use process cannot be effectively reflected. The method comprises the following steps: receiving user input through an interaction end, recording agent response time, setting a learning time reference, obtaining processing time, calculating a processing learning ratio by utilizing the processing time and the learning time reference, classifying agent states in combination with the response time, and judging whether to enter a pair training; detecting a user instruction, calling an instruction answer benchmark, recording an agent answer, setting recording time and generating a training score within the time after the user enters a pair exercise; the memory occupation is detected in real time, the inscribing variation is calculated, the training effect is analyzed in combination with the training score and the memory change, and whether the training transfer is performed or not is judged according to the analysis result, so that the agent training efficiency is improved.

This invention relates to the field of tunnel construction technology, and more particularly to a system and method for dynamically optimizing tunnel construction parameters based on geological information from point cloud data. At multiple monitoring time points, point cloud data is collected from the tunnel segment to be constructed, obtaining multiple point cloud datasets. The tunnel segment is divided into multiple construction areas, and multiple regional point cloud datasets are obtained from these datasets. Point cloud change analysis is performed on each regional dataset to obtain multiple point cloud change rates. Based on these regional point cloud datasets, reflection intensity analysis is conducted to obtain multiple reflection intensity coefficients. Combined with the multiple point cloud change rates, geological analysis is performed to obtain the distribution of concealed geological information. Based on this distribution, tunnel construction parameters are dynamically optimized to obtain optimized tunnel construction parameters for tunnel construction. This achieves the technical effect of improving the efficiency and safety of tunnel construction while reducing construction risks and costs.

A multi-parameter feedback-based intelligent control method and system for aquaculture wastewater, relating to the field of wastewater treatment and control technology, includes: acquiring key water quality monitoring indicators for each treatment subsequence; real-time monitoring of each treatment subsequence; critical change analysis of historical monitoring periods marked as abnormal for the treatment subsequences, obtaining critical feature sets for historical monitoring periods, comparing significant differences in the critical feature sets, and constructing a critical correlation feature network of abnormal indicators for abnormal historical monitoring periods; pseudo-correlation analysis of the critical correlation feature network, obtaining pseudo-correlation nodes and interference nodes, and constructing a critical directed acyclic graph and critical interference link graph of abnormal indicators; constructing a multi-device collaborative control model based on the critical directed acyclic graph and critical interference link graph of several abnormal indicators, outputting specific control parameters of the associated devices for each treatment subsequence and performing preventive control to achieve efficient, economical, and stable treatment of aquaculture wastewater.

The invention relates to the technical field of data processing, in particular to a data quality analysis method, system and device and a storage medium. The data quality analysis method comprises the steps of obtaining training data; inputting the training data into a neural network model to execute a model training operation so as to obtain data processing information of the neural network model on the training data, the data processing information comprising a blood relationship graph of the training data and quality information of the training data in each processing link of model training; inputting the blood relationship graph of the training data and the quality information of the training data in each processing link of model training into a data quality change analysis model, and outputting a quality change result of the training data in each processing link of model training by the data quality change analysis model; and determining a data quality analysis result according to the data quality change result. According to the method, the specific processing link causing the quality reduction of the training data can be quickly positioned.

The present invention relates to a device for automatically detecting changes in a contract and assessing risks, which may be used in the fields of legal risk management, contract review, compliance monitoring, and the like and, more specifically, to a device for automatically detecting changes in a contract and assessing risks that utilizes artificial intelligence (AI) and legal data analysis technologies to automatically detect changes in a contract and evaluate legal and business risks of the changes. A device for automatically detecting changes in a contract and assessing risks, according to one embodiment of the present invention, comprises: a content classification module; a change detection module; a risk assessment module; and a change analysis and reporting module.

The invention provides an airborne system ICD change method and system, and relates to the field of airborne systems.The airborne system ICD change method comprises the following steps that S1, an airborne system ICD change management environment is initialized, and an interface dependency relationship model is established; s2, receiving a change request, analyzing the change request, and identifying a change type; s3, calling the interface dependency relationship model, executing change influence analysis based on the change type, and generating a change influence report; s4, performing change review and implementation based on the change influence report to obtain a change result; and S5, verifying the change result, and generating a change closed-loop report. The problems that in the ICD changing process of an existing airborne system, the flow is not standard, changing analysis is not comprehensive, different types of ICD changing lacks a targeted method, and changing system collaboration is insufficient are solved, the scientific, controllable, efficient and accurate changing method and system are provided, and the compatibility and reliability of the changed system are guaranteed.

This invention discloses a wetland landscape pattern classification method based on optimized feature parameters. First, multispectral and topographic data of the target wetland are preprocessed to extract feature parameters from the preprocessed data. Wetland landscape categories are defined, identifying 13 land cover types. Training samples are determined by referencing field survey data, original multispectral image data, principal component analysis (PCA1) of original remote sensing data, and the tasseled cap transformation brightness component of original remote sensing data. For the preprocessed multispectral data, wetland information extraction is performed using both maximum likelihood classification and decision tree classification. The classification results from the two extractions are combined with the extracted feature parameters to form fused data. Information extraction based on maximum likelihood classification is then performed on the fused data to obtain dynamic change analysis results of wetland landscape classification. Combined with optimized feature parameters, multiple feature parameters are fused to achieve information extraction from remote sensing images and refined classification of wetland landscapes.

The invention provides an ocean multi-parameter water quality synchronous surveying and mapping and dynamic monitoring method and system based on GNSS positioning, and relates to the technical field of intelligent control, and the method comprises the steps: carrying out the spatial correction of first water quality parameter data after interference compensation through a correction value, so as to obtain the corrected first water quality parameter data; performing space-time matching processing on the corrected first water quality parameter data and the second water quality parameter measurement data to generate a synchronized water quality parameter data set corresponding to the real-time position information; based on the synchronized water quality parameter data set, performing water quality dynamic change analysis to obtain an analysis result; and when the analysis result meets a preset early warning condition, red tide early warning information is generated and issued. According to the invention, the red tide can be monitored and early warned more timely and accurately.

This application provides a method for inverting the dynamic changes of the seabed sedimentary environment based on three-phase potential, including in-situ data processing, electrical signal calibration, mathematical model establishment, and dynamic change analysis. By deploying a seabed electrode array, signals such as spontaneous potential, resistivity, and redox potential are acquired in real time. An inversion algorithm is used to deduce seabed sedimentary environment characteristics, such as seabed interface location, suspended particle concentration, sediment density, porosity, and water content. This method, combined with multi-frequency signal analysis, can monitor changes in the seabed sedimentary environment in real time and identify sediment movement. Compared with existing technologies such as CN118153411B and CN110411923B, this invention covers richer inversion content, and the complementarity of potential signals improves monitoring accuracy and efficiency, exhibiting stronger adaptability and reliability. This method has lower equipment and maintenance costs, is suitable for large-scale, long-term monitoring, and can provide innovative solutions in fields such as deep-sea monitoring, environmental assessment, and resource exploration.

This technology provides a way for users to easily select and change analysis themes and targets in consumer behavior analysis. [Solution] The information processing device (10) includes a selection data receiving unit (13) that receives selection data from the user terminal, which is selected on a selection screen that includes options for selecting an analysis theme for consumer behavior data showing the consumer's history of consumer behavior and attributes, and options for selecting data to be analyzed in the consumer behavior data; a prompt generating unit (14) that generates a prompt including text instructing analysis on the analysis theme indicated by the selection data and text indicating the storage location of the data to be analyzed indicated by the selection data; and an analysis result transmitting unit (15) that transmits analysis results based on the output obtained by inputting the prompt into a generation model to the user terminal (20).

The invention discloses a network clue data change analysis method and system based on a knowledge graph, particularly relates to the technical field of data processing, and is used for solving the problem that a clue coordinate mapping result does not conform to an actual geographical current situation due to dependence on a static geographical entity knowledge graph in the prior art. The method comprises the following steps: describing and identifying spatial differences by aggregating multi-platform clue positions, and generating a change pre-check instruction when the differences relate to geographic entities in a preset range; performing topological manifold embedding analysis on the text in combination with the initial coordinates to generate a manifold embedding distance, and detecting a conflict rate of a spatial reference system; when the distance or the conflict rate exceeds a threshold value, triggering knowledge graph updating; and finally, re-matching based on the updated map to obtain a target geographic entity and coordinates. Real-time perception of geographic entity change and dynamic map correction are realized, and the accuracy and reliability of natural resource clue space positioning are effectively improved.

The application discloses a kind of methods for simulating the dynamic fate distribution of pollutants in lake supplied by reclaimed water, and relates to the technical field of lake pollutant simulation distribution, comprising the following steps: establishing a lake supply simulation device, simulating the supply of reclaimed water to the lake, and collecting simulation data to obtain pollutant simulation change data;And unit division processing is carried out to obtain concentration diffusion unit data, and peak concentration analysis is carried out to obtain peak concentration distribution data;And distribution change analysis is carried out to obtain pollutant distribution change data;Establish a concentration prediction model to predict the time and area of the occurrence of the peak concentration of pollutants;The application is used to solve the problem that when the dynamic distribution of pollutants in the lake supplied by reclaimed water is obtained, it mainly depends on manual sampling, it is difficult to capture the dynamic change of the diffusion of pollutants in the lake, and the discharge scheme of reclaimed water lacks reliable scientific basis, and the lake may cause water quality to exceed the standard due to excessive discharge and improper discharge time.

This invention proposes a resource allocation method and system for dynamic prediction of certification risks based on big data, relating to the field of certification data analysis technology. It acquires enterprise data and enterprise data package information; performs credit risk characteristic analysis, risk prediction, and model output accuracy analysis; triggers enterprise risk prediction instructions; performs data prediction, credit risk characteristic analysis, and risk prediction on current enterprise certification information; acquires current enterprise risk assessment data and its model accuracy analysis data; performs model accuracy change analysis; triggers sample tracing instructions; evaluates and verifies current enterprise prediction data package information; obtains data package prediction verification results; triggers model update analysis; obtains updated enterprise risk assessment data; performs audit configuration and updates based on enterprise risk assessment data; and obtains enterprise audit frequency. This invention achieves intelligent and accurate prediction and allocation of enterprise certifications.

The invention discloses a remote sensing image change detection method and equipment based on structure perception and frequency domain fusion, belongs to the technical field of image change detection, and realizes space alignment and lightweight feature extraction of dual-time-phase features through a dual-branch multi-layer feature extraction encoder sharing weight. A complementary enhancement mechanism is constructed between a frequency domain and a spatial domain by using a structure-perceived frequency domain change module and a multi-level frequency domain fusion decoding module. And false change interference can be effectively suppressed, and the recognition capability of building boundaries and detail areas is enhanced. The whole structure gives consideration to detection precision, generalization performance and calculation efficiency, has good engineering applicability, and can be popularized and applied to various remote sensing scenes such as urban building dynamic monitoring, land utilization change analysis and post-disaster emergency evaluation.

The present application belongs to the oil and gas development industry oil and gas production engineering technical field, especially relates to a kind of strong speed sensitive reservoir particle migration productivity damage prediction method.The present application is by to the pre-processing of oil well production dynamic data, establishes a kind of pre-processing production dynamic data method to remove the influence of engineering intervention on productivity, can effectively reflect the productivity decline trend of reservoir under the condition of natural attenuation, improve the accuracy of productivity change analysis caused by particle migration factor;And based on production dynamic data calculation particle migration decline rate, provide the basis for the productivity decline damage caused by particle migration quantification;At the same time, the productivity ratio under the action of particle migration, productivity damage rate and damage rate calculation method are proposed, which can realize the quantitative characterization of the degree of reservoir productivity loss caused by particle migration, provide the basis and technical support for the prevention and control of particle migration measures, and have important engineering application value.

An apparatus for analyzing a laser process, the apparatus including a sensor module configured to acquire an optical signal generated during a laser process of a target, and a processor configured to detect an abnormality of the laser process through an instantaneous change analysis process of the optical signal performed whenever the optical signal is acquired by the sensor module, and a longitudinal change analysis process of the optical signal performed at a time point when a target time section ends, the target time section being a time during which the laser process is performed.

This application provides a method, device, medium, and program product for identifying change risks, relating to the field of software release and maintenance technology. The method includes: in the process of identifying change risks, performing structured analysis on multi-source material data based on a risk analysis model and according to the first analysis prompt, extracting a change analysis summary that can characterize the semantics of the change, which can comprehensively and accurately capture change risks at different levels, and recalling corresponding risk knowledge items from the risk knowledge base based on the change analysis summary, greatly expanding the coverage and benchmark of risk knowledge, and further performing correlation reasoning through the risk analysis model, reasoning based on the change content and historical knowledge (i.e., risk knowledge items, etc.), generating a more accurate risk judgment that is more in line with the specific change, effectively improving the accuracy of risk identification.

The application relates to a public opinion intelligent monitoring and analyzing method, device and computer equipment for multi-platform interaction. The method comprises the following steps: obtaining current public opinion monitoring data of each platform and platform user distribution information of each platform, and extracting public opinion feature information of each platform through a public opinion feature extraction strategy based on the current public opinion monitoring data of each platform; identifying user population proportion information of each platform based on the platform user distribution information of each platform, and identifying public opinion change trend information of each platform through a public opinion change analysis strategy based on the public opinion feature information of each platform and the user population proportion information of each platform; constructing a comprehensive public opinion change correlation graph through a multi-platform public opinion interaction correlation strategy based on the public opinion change trend information of each platform, and predicting public opinion risk information through a public opinion risk analysis strategy based on the public opinion change correlation graph. The method can improve the accuracy of public opinion monitoring and analysis of multiple platforms.

The invention relates to the field of edge data transmission, in particular to a data processing system and method based on big data, and the system comprises a node monitoring module which is used for determining whether to carry out node processing analysis for each edge processing node or not according to a transmission fluctuation index and a supervision fluctuation index; the analysis and evaluation module is used for determining a processing and analysis mode according to the execution interference index and the execution duration index; the production analysis module is used for determining a change analysis strategy according to the branch change generalization coefficient and determining whether each initial analysis node is in a third node risk state or not according to the change reference interference parameter; the interference analysis module is used for determining a data redundancy coefficient according to the estimated key proportion index and the topological estimated key index; and the execution optimization module is used for determining whether to perform dynamic execution analysis on the execution analysis node according to the node execution duration coefficient. According to the invention, the transmission efficiency of big data real-time transmission in the industrial production process is improved.