46 results about "Classification rule" patented technology

This application provides an object segmentation method and an object segmentation model training method, which can be applied to the field of artificial intelligence technology. The object segmentation method includes: determining whether the current video frame in a video frame sequence is a keyframe, a regular frame, or a frame to be inspected based on a preset classification rule; if the current video frame is a keyframe, extracting features from the current video frame to obtain the current frame image features; if the current video frame is a regular frame or a frame to be inspected, determining the motion change features of the current video frame relative to a reference keyframe associated with the current video frame, and determining the current frame image features based on the motion change features and the reference image features; and performing object segmentation on the current frame image features based on the target mask features representing the target object to obtain the object segmentation result of the current video frame, wherein the object segmentation result indicates the position and shape of the target object.

The application discloses an online checking method and system for an SF6 gas detector, and the method comprises the following steps: controlling a standard gas source to output an asymmetric triangular concentration waveform, wherein the rising rate of the waveform is not equal to the falling rate; collecting real-time concentration of the detector; drawing rising and falling response curves with standard concentration as the horizontal coordinate and real-time concentration as the vertical coordinate; calculating the deviation area between the two curves and an ideal straight line; if the area ratio is not greater than a dynamic threshold, extracting all intersection points of the two curves and sorting them; calculating the algebraic area of the region surrounded by adjacent intersection points to generate a surrounding area symbol string; and determining the fault type according to the intersection point number parity and zero value, intersection point horizontal coordinate interval dispersion degree and symbol string distribution according to the topological classification rule. The asymmetric excitation fully exposes the adsorption-desorption asymmetric characteristics of the sensor, and the response curve topological characteristics realize online identification and classification of baseline separation, translation drift, response lag, nonlinear superposition and noise jamming and the like.

This invention discloses a distributed system and method for a pathological slide scanner. The system, used to operate a high-throughput pathological slide scanner, includes: a distributed control system for placing pathological slides at designated positions on the scanner, scanning the slides to convert them into digital results, and automatically sorting and categorizing the scanned slides according to predetermined classification rules; and a distributed auxiliary monitoring system for assisting the scanner's operation, monitoring the distributed control system's operation and any abnormalities, and monitoring the overall system temperature, providing feedback and adjustment in case of abnormal temperature rise. This invention effectively solves the problems of tedious, time-consuming, and labor-intensive small-batch scanning, as well as the load and temperature rise issues that easily occur when equipment operates continuously for extended periods in high-throughput scanning, providing fast and smooth automated high-throughput pathological slide scanning capabilities.

This invention provides a digitally intelligent multi-terminal device collaborative unmanned self-service hotel system, comprising: an access control terminal integrating a multimodal information collection unit, which classifies visitor types into guests, authorized visitors, service personnel, and unauthorized personnel according to preset classification rules, and generates encrypted electronic vouchers with attribute tags; based on the attribute tags of the electronic vouchers, it opens exclusive service ports according to visitor type; it generates dynamic and time-limited access vouchers for authorized visitors and service personnel; and it uses intelligent monitoring equipment deployed in the hotel's public areas to perform visual recognition and trajectory tracking of unauthorized personnel. This invention simplifies the overall hotel management process and achieves a comprehensive improvement in operational efficiency, security, and customer experience through intelligent and unmanned design, providing reliable technical support for the digital transformation of the hotel industry and possessing significant practical application value.

The application discloses a kind of multi-modal juvenile idiopathic scoliosis screening methods based on back RGB-D image, belong to image processing and scoliosis screening technical field, specifically include: acquisition subject is under the RGB-D image pair of Adams forward bending posture, RGB color image is artificially labeled, construct and train back key point detection model, establish the calculation rule of maximum trunk rotation angle, minimum trunk rotation angle and back profile asymmetry index, establish AIS classification rule based on RGB-D dataset, and then complete the AIS classification of the subject to be detected.The application is a kind of non-contact radiation-free AIS screening method, utilizes the complementary mode of two kinds of modal data of RGB-D, realizes the comprehensive utilization of back two-dimensional, three-dimensional information, makes up the problem of feature missing under single mode, with the characteristics of fast and efficient, robust objective.

This invention relates to the field of data governance technology, specifically to an intelligent inventory system for medical data resources. The system comprises: first, performing connection testing, collection scope detection, and access permission assessment on the target data source, and collecting medical metadata to form a metadata set; then, performing semantic association analysis and data lineage analysis on the metadata set, and generating classification results and corresponding evidence chains by combining data classification standards, data classification rules, and an intelligent recognition model; finally, outputting the data resource inventory results, and performing verification and feedback updates when inconsistencies are identified or when manual confirmation instructions are received. This invention can improve the completeness of metadata collection, classification accuracy, and result traceability.

This invention discloses a method and terminal for rapidly screening a set of anticipated faults in a power grid. The method identifies the target branch that will trigger a Level 1 fault in the power grid system. Based on the backup protection of any branch other than the target branch, a cascading trip risk margin is created to indicate whether the branch will trigger a cascading trip. Based on the node voltage and reactive power of any branch other than the target branch, a static voltage stability margin is created, representing the degree to which changes in reactive power cause node voltage fluctuations. Screening and classification rules are set according to different values ​​of the cascading trip risk margin and the static voltage stability margin. Based on these rules, all branches other than the target branch are screened to obtain the set of anticipated faults. This invention focuses on rapidly and accurately screening high-risk faults in power grid branches before and after a fault occurs during power system security analysis, thus completing the screening of the anticipated fault set.

This invention discloses a service assurance method and system for door lock collaboration. The method includes: generating a protection request message and sending it to a router based on the first door lock detecting an abnormal state of a target object, and assigning it a medium-priority protection strategy; based on the protection request message, other door locks enter a waiting-to-respond state, and the router, by identifying data streams matching classification rules on different ingress interfaces, counts the number of active door locks to reach a preset threshold, and upgrades the priority of the data stream corresponding to the event from medium priority to high priority; any responding door lock detects that the target object's state has returned to normal, sends an exit-of-concern message to the router, and when the number of exit-of-concern messages reaches a preset exit threshold, notifies all door locks to stop detection and data stream transmission. Using this invention, accurate identification of abnormal events, on-demand upgrades of network resources, and automatic recovery of system state can be achieved, improving the reliability of security response and network resource utilization.

This invention belongs to the field of computer storage system architecture technology, and provides a heterogeneous storage acceleration system and method for edge AI computing. The technical solution includes a main processor for initiating storage access requests; a three-tiered heterogeneous storage unit, comprising a dedicated AI model cache, a hybrid storage pool, and a data cache module; and a hardware intelligent scheduler connected to the main processor and the three-tiered heterogeneous storage unit, including: a data feature recognition module for extracting feature vectors from storage access requests and classifying them into AI model, video stream, or system data categories based on preset classification rules, and adding data classification labels; and a storage routing decision module for performing differentiated storage routing decisions based on data type and arbitrating concurrent requests to ensure the highest priority for AI model requests and deterministic bandwidth for video stream requests. Optimal matching of data streams and storage resources is achieved through hardware logic.

This invention discloses a geological experimental pretreatment method for PDC drill cuttings, comprising: cleaning the acquired cuttings sample; identifying and removing false cuttings such as fragments and solidified mud particles by quantifying and judging the physical and visual characteristics of the cuttings based on preset identification rules, ensuring the authenticity of the sample; performing refined lithological classification on the remaining true cuttings based on classification rules, such as distinguishing between carbonate rocks and clastic rocks; and selectively identifying target cuttings from the classified true cuttings according to the specific geological experimental purpose. This invention establishes a standardized processing procedure that can significantly improve the purity and stratigraphic representativeness of cuttings samples, thereby ensuring the accuracy and reliability of subsequent geological experimental analysis data.

The application provides a dynamic adaptive data stream acceleration transmission method and device for a signal creation environment. The method comprises the following steps: detecting the capabilities of a central processing unit, an operating system, a network interface and a cryptographic acceleration unit in a signal creation computing node to obtain environment capability information, and organizing the environment capability information into a signal creation environment capability profile; analyzing the service type, data size, timeliness level and security level of a data stream, and combining a preset classification rule to generate a data stream profile corresponding to the data stream; collecting running state information across layers and organizing the running state information into a running state vector; based on the signal creation environment capability profile, the data stream profile and the running state vector, executing a preset strategy decision process to determine a transmission strategy parameter set for the data stream; and sending data fragments according to the transmission strategy parameter set. The application can improve the utilization rate of signal creation environment resources, improve the transmission efficiency of multiple types of data streams and reduce the manual optimization overhead of transmission parameters.

The present disclosure relates to a webpage classification method and device, medium and electronic equipment, to solve the problem that the webpage cannot be classified according to the webpage production mode in the related art. The method comprises: obtaining page information of a target webpage; matching the page information of the target webpage with a preset classification rule to obtain a target classification result of the target webpage, wherein the preset classification rule comprises a classification rule based on a webpage production mode, and the webpage production mode comprises at least one of a platform template production mode, a website building production mode and an independent station production mode.

This invention provides a method for analyzing negative Weibo comment data based on a cosine similarity-C4.5 decision tree, comprising: Step S1, preprocessing the original Weibo comment data, identifying whether the comments contain keywords to form a complete descriptive attribute set using the AC automaton algorithm, and labeling the influence category based on the number of comment interactions; Step S2, using the AC automaton algorithm to perform multi-keyword fast matching on the comment text; Step S3, based on the improved C4.5 algorithm, first merging attribute values ​​with similar information entropy using cosine similarity measurement, then calculating the information gain rate of each attribute and recursively constructing a decision tree; Step S4, using a pessimistic error pruning algorithm based on confidence interval estimation to perform post-pruning on the decision tree and extract classification rules. This invention improves retrieval efficiency through the AC automaton, reduces model redundancy through cosine similarity merging, and enhances generalization ability through pessimistic pruning. The three synergistically achieve a simultaneous improvement in classification accuracy, model simplicity, and processing efficiency.

This application discloses an article classification method, apparatus, electronic device, and storage medium, relating to the field of artificial intelligence technology or other related fields. The method includes: acquiring at least one target article to be classified; performing topic analysis on the target article using a preset model to generate topic tags; calling a classification tag document and querying the domain to which the topic tags belong in the classification tag document to obtain the domain tags of the target article; querying all topics involved by the topic tags and domain tags in the classification tag document to obtain a candidate topic set, and combining the preset model and the candidate topic set to perform topic analysis on the target article to generate topic tags; summarizing the domain tags, topic tags, and topic tags to generate the article classification result for the target article. This application solves the technical problem in related technologies where reliance on manual labeling and fixed classification rules leads to low accuracy in article classification.

This invention discloses a risk classification and identification method applied to open-cut foundation pit engineering in rail transit, relating to the field of rail transit engineering construction safety technology. The method includes: acquiring a multi-dimensional monitoring dataset during the construction process of the open-cut foundation pit project; determining the structured data corresponding to various types of monitoring data based on the multi-dimensional monitoring dataset; establishing an analysis and calculation model based on preset classification rules; analyzing and calculating various types of monitoring data in the structured data according to the analysis and calculation model to obtain the sub-item level values ​​corresponding to each type of monitoring data; and determining the comprehensive evaluation level of the open-cut foundation pit project based on all sub-item level values. This invention can improve the datafication and standardization of the risk identification process, significantly improving the accuracy and reliability of risk classification and identification in open-cut foundation pit engineering for rail transit.

The present application relates to the field of data processing, and particularly relates to a business vehicle model library system generation method, device, equipment and medium. The present application generates a structured demand through semantic word segmentation and intent recognition, constructs a unified channel-city-classification mapping relationship based on the structured demand, replaces independent standards of each channel, and solves the problem of non-uniform standards among channels. Secondly, the associated configuration supports flexible setting of classification rules according to the city dimension, breaks the solidified logic of national uniformity, and meets the differentiated operation needs of multiple channels. Thirdly, the whole-process rule automatic execution does not require manual intervention from demand analysis to conflict processing, solves the pain points of low efficiency and easy errors of manual maintenance. Finally, the standardized classification mechanism can quickly configure the minimum level for new categories-vehicle series, make up for the defects of the missing adaptation mechanism, ensure timely supplement of new operation capacity, and realize efficient management and application of vehicle data.

Provided are an environmental temperature change prediction device and a prediction method for a machine tool. The environmental temperature change prediction device (7) includes: an environmental temperature acquisition unit (8) that acquires an environmental temperature by means of a temperature sensor (5, 6); an outside air temperature acquisition unit (9) that acquires an outside air temperature by means of a temperature sensor (4); a factory environmental pattern setting unit (10) that defines a classification rule and an environmental temperature prediction model in advance as a factory environmental pattern, the classification rule classifying a change tendency of the environmental temperature into a plurality of patterns based on data of the environmental temperature and the outside air temperature of a factory, and the environmental temperature prediction model being different for each pattern; a prediction model generation unit (11) that selects a suitable factory environmental pattern from the classification rule based on data of a past environmental temperature and / or outside air temperature of the factory, and determines parameters of the corresponding environmental temperature prediction model; and an environmental temperature change prediction unit (13) that predicts a change in the future environmental temperature by means of the generated environmental temperature prediction model.

This invention discloses a method for constructing a terrain-level basic geographic entity data model, comprising: acquiring surveying and mapping geographic information, including remote sensing images, elevation data, and geomorphic classification data; obtaining terrain rasters based on elevation data from different time phases using remote sensing images; dividing terrain semantic units according to the terrain rasters; extracting terrain change semantic categories of terrain blocks using geomorphic classification data; outputting vector surface boundaries of remote sensing image pairs and terrain rasters labeled with the terrain change semantic categories through a centroid network; obtaining spatial association results between geographic entities and terrain semantic units based on the vector surface boundaries; assigning terrain semantic attributes to entities based on the spatial association results; and constructing a terrain-level basic geographic entity data model through neural symbol fusion. This method utilizes multi-scale signal-to-noise ratio adaptive weighting and hard classification rule constraints to enhance semantic adaptation to terrain changes and improve the accuracy and interpretability of geographic entity data modeling.

This application provides a data classification method, apparatus, device, and storage medium, applicable to scenarios such as data generation. The method includes: displaying a data input interface and receiving a classification rule standard text and N unclassified data points input by a first object in the data input interface; selecting P confusing data points from the N unclassified data points based on the classification rule standard text, and determining Q confusing classification pairs corresponding to these P confusing data points; displaying a rule supplement interface showing these Q confusing classification pairs; receiving supplementary classification rule text for the Q confusing classification pairs input by the first object in the rule supplement interface; and determining the classification result of the P confusing data points based on the supplementary classification rule text and the classification rule standard text. In other words, this application can improve the accuracy and efficiency of classifying difficult data, and through a visual interface, transform complex classification work into simple interactive operations, lowering the professional threshold.

This invention discloses a main grid monitoring method based on event-driven intelligent analysis, comprising: collecting raw alarm signals and related measurement data reported by the monitoring system; classifying the raw alarm signals and related measurement data according to a preset classification rule base, generating standardized alarm signals with fault labels, and then performing information filtering and related signal fusion operations to generate comprehensive alarm events; further generating structured fault events by performing event matching and probabilistic reasoning through a Bayesian network inference algorithm based on a preset event knowledge base and power grid topology; subsequently initiating and executing an intelligent leak prevention monitoring mechanism to generate leak prevention monitoring closed-loop records; and generating standardized event archives and updating the event knowledge base based on the leak prevention monitoring closed-loop records, thereby realizing closed-loop management of main grid monitoring based on event-driven intelligent analysis. This invention constructs a monitoring closed loop from perception and analysis to continuous optimization, realizing intelligent and precise main grid monitoring.

This invention relates to the field of video editing technology, and provides a method, apparatus, device, and medium for optimizing categorized electronic photo albums of family images. It solves the problem that currently automatically generated electronic photo albums cannot meet the diverse needs of users, leading to low user engagement. The method includes: acquiring a target video and user operation information for each electronic photo album corresponding to various automatically generated image types; optimizing a preset image classification rule based on the operation information to obtain a target classification rule; classifying each frame of the target video according to the target classification rule to obtain target image groups corresponding to each image category; and generating target electronic photo albums corresponding to each target image group based on each target image group, each electronic photo album, and the images already existing in each electronic photo album. The electronic photo albums obtained through this method are more in line with user preferences and usage habits.

The application discloses a kind of laser beam energy distribution self-adapting modeling method and system, belong to intelligent laser processing and digital twin field.The method is extracted by laser focal plane heat flux density distribution data processing, feature vector describing beam energy distribution characteristics;Optimal energy distribution model is intelligently recommended using random forest machine learning algorithm to analyze the classification rule of feature vector;Based on Levenberg-Marquardt optimization algorithm, the model parameters are accurately fitted;The beam model is compiled as a heat source model and loaded into the simulation platform for execution, and the model is verified and continuously optimized through virtual-real data comparison.The application realizes the adaptive construction and optimization of laser processing beam model, and provides a high-precision model basis for intelligent manufacturing.

This invention provides a method and related apparatus for generating diagnostic point tables for fieldbus devices, belonging to the field of industrial automation diagnostic technology. The method includes: parsing the fieldbus data stream to obtain a diagnostic information feature vector containing a data source identifier, function code, and parameter index; mapping the diagnostic information feature vector to a preset diagnostic information classification rule base to obtain diagnostic information items with physical meaning categories; standardizing and packaging the diagnostic information items based on a preset packaging rule base to generate a structured diagnostic data package; performing mapping and conversion based on a preset diagnostic point table standard format to obtain a diagnostic point table file conforming to the standard format; further establishing a dynamic association mapping between diagnostic point identifiers and the real-time status of the device, constructing a device status transition matrix, and realizing real-time updates of the diagnostic point table according to changes in device status. This invention solves the problems of scattered and inconsistent formats of diagnostic information by automatically parsing and standardizing the packaging of the physical meaning of diagnostic information, achieving standardized management and dynamic adaptation of diagnostic data, and significantly improving the efficiency and accuracy of diagnostic data processing.

This invention provides a raindrop spectrum inversion method that comprehensively considers environmental factors, comprising the following steps: acquiring dual-polarization radar base data for the corresponding region; performing initial raindrop spectrum inversion based on the dual-polarization radar base data using Gamma distribution; performing unsupervised classification using K-means clustering algorithm to generate raindrop spectrum classification labels; constructing an environmental feature matrix; using environmental features as input and raindrop spectrum classification labels as prediction targets to generate dominant factors influencing raindrop spectrum morphology changes and corresponding classification thresholds; constructing an IF-THEN-style classification rule base based on the dominant factors and classification thresholds; using the environmental data corresponding to the rainfall to be predicted as input to the classification rule base, classifying the rainfall to be predicted to the preset raindrop spectrum classification labels, and performing precipitation monitoring and forecasting. This invention improves the accuracy of raindrop spectrum inversion by refining the classification of rainfall events, reducing the impact of multiple factors on the inversion of key raindrop spectrum parameters.

The present application relates to the technical field of coal mine geology engineering, in particular to a coal seam roof and floor equivalent lithology determination method based on drilling columnar chart information, which can extract all straight line objects and text object data in the drilling columnar chart in a software manner, match the text and rock stratum information by classifying the text objects into the areas divided by the corresponding vertical straight lines according to the horizontal positions, construct a table framework combined with the straight line objects, extract the sequence number, dip angle, true thickness and lithology data of each rock stratum, determine the coal seam roof and floor equivalent lithology based on the lithology description recognition, lithology classification rules and algorithms, and finally output the structured rock stratum data and equivalent lithology results. The present application has the beneficial effects of greatly improving the efficiency of the exploration drilling columnar chart information reading and processing, significantly reducing the subjective error of manual interpretation, realizing the accurate analysis of the rock stratum data, ensuring the accuracy and consistency of the coal seam roof and floor equivalent lithology determination, and laying an important foundation for the mine gas accuracy prediction.

The application provides a kind of laser coaxial fuse process wire and substrate transition state adjustment method and system, wherein the method constructs reference parameter set, transition state classification rule and wire feeding speed control rule through preparation test stage, in control printing stage, real-time acquisition target wire feeding speed, actual wire feeding speed and resistance value between wire and substrate, combined with the above rule, transition state is judged and wire feeding speed adjustment instruction is generated, accurate interpretation of transition state and in-situ regulation of process parameters are realized.The application uses actual wire feeding speed and resistance signal to monitor cooperatively, has the advantages of fast signal acquisition speed, accurate multi-data comprehensive interpretation and wide material applicability, and has important significance for solving technical problems such as narrow process window, poor process consistency and unstable quality of laser coaxial fuse additive process.

This invention discloses a method and system for predicting and warning of wind power anomalies under extreme weather conditions, belonging to the field of renewable energy power generation technology. An initial operating dataset is constructed by collecting meteorological condition variables and operating parameters of the wind power generation device; the dynamic correlation between wind speed changes and power output is extracted to determine the response delay time of wind speed changes to power fluctuations, obtaining wind speed change trends and mechanical inertial response indices; power anomaly prediction is performed, and when the prediction result exceeds a first threshold, the corresponding time period is marked as a potential power anomaly event; the degree of interaction between the mechanical inertial response and meteorological condition variables is quantified to generate a corresponding power anomaly event intensity assessment index; combined with preset classification rules, the warning level is determined, and a warning signal is triggered and output; this invention improves the accuracy of wind power anomaly prediction under extreme weather conditions by quantifying the dynamic interaction between wind speed fluctuations and turbine mechanical inertia.

The application relates to the technical field of voice processing, in particular to a voice enhancement method and system of a loudspeaker. The method comprises the following steps: acquiring a sound signal, performing frame processing, extracting multi-dimensional voice features, presetting a classification rule, outputting a human voice confidence, generating human voice existence information; acquiring a loudspeaker reference signal, performing acoustic echo cancellation processing to obtain an echo cancellation output signal, and adjusting an adaptive update strategy according to the human voice confidence when human voice exists, namely, freezing adaptive filter coefficient update and / or reducing the update strength of the adaptive filter; identifying a main noise frequency band of fluctuant noise, performing noise suppression processing to obtain a noise suppression output signal; acquiring state information, adjusting update parameters and / or suppression strength, and outputting a voice-enhanced loudspeaker signal. The method solves the problem that an existing loudspeaker system is difficult to effectively adapt to background noise and echo influence in a complex acoustic environment, thereby causing the intelligibility of voice to decrease.