175 results about "Coverage data" patented technology

The invention relates to the technical field of landscape evaluation, and discloses an urban green land landscape evaluation method based on a large model, and the method comprises the steps: carrying out the real-time analysis and standardization processing of a streetscape image, IoT environment data, satellite vegetation coverage data and RTK high-precision positioning information of a target city district, extracting core landscape elements, building cross-scene semantic mapping, and carrying out the calculation of the cross-scene semantic mapping. Transmitting the standardized data to a central database and deploying edge nodes; extracting a multi-dimensional landscape index by adopting an improved semantic segmentation model, dynamically adjusting an index weight in combination with regional features and seasonal changes, and classifying and correcting deviation data by edge nodes; a visual evaluation result is generated based on a cooperative computing architecture and a digital twinborn model, a landscape space to be promoted is identified, and optimization suggestions are generated; and obtaining planner feedback information, updating the model, the weight rule and the suggestion generation strategy, and forming a closed loop iteration mechanism. According to the method, the dynamic and practical evaluation requirements of the current urban green land landscape can be met.

Disclosed are a three-dimensional laser point cloud-based method and system for in-depth vegetation management in transmission corridors. The method comprises: collecting multi-source data by means of an unmanned aerial vehicle- and helicopter-mounted multi-sensor system, and preprocessing the multi-source data; using the processed multi-source data to create a digitalized power grid corridor and construct a vegetation management analysis model; on the basis of data analyzed by the vegetation management analysis model and geofencing technology, designing a hazard vegetation clearing-cost-compensation prediction model; and developing a mobile application for analyzing hazard vegetation data flows and the closed-loop management of vegetation management service flows. The described method achieves high-precision and high-coverage data collection, precisely identifies transmission line digital twins and hazard vegetation, standardizes and automates the management of hazard vegetation clearing and related compensation, and develops a mobile application for analyzing hazard vegetation data flows and the closed-loop management of vegetation management service flows, thereby achieving the end-to-end digital and mobile management of vegetation management. The organic combination of steps comprehensively improves the intelligence and efficiency of transmission line vegetation management.

The invention relates to the field of industrial automation testing, discloses a multifunctional testing tool and method for an EUROMAP interface of an injection molding machine, and achieves the crossing from single function verification to system-level compliance evaluation. A test network is constructed through a controller, and deep compliance verification, coverage data interaction, exception handling and cross-layer response consistency are realized. The test tool integrates the functions of protocol analysis, signal simulation, fault injection and the like, supports dynamic generation of boundary value test scenes and abnormal injection of signal delay, CRC errors and the like, and verifies the time sequence / logic consistency of a protocol instruction and an execution mechanism response through a hardware-level timestamp alignment technology. According to the method, an evaluation report including compliance rating, fault diagnosis and optimization suggestions is automatically generated, the problems of single coverage dimension, insufficient abnormal simulation, cross-layer verification deficiency and the like of a traditional test are solved, the intelligence and standardization level of the injection molding machine interface test is remarkably improved, and the equipment interconnection and intercommunication performance is guaranteed.

The invention provides an individual credit risk assessment method, system and device based on federal learning, and belongs to the technical field of data processing. The method comprises the following steps: in response to a credit evaluation request from a credit evaluation node, determining one or more evaluation participation nodes of a credit evaluation object; generating a corresponding local credit evaluation instruction and sending the local credit evaluation instruction to each evaluation participation node; wherein the local credit assessment instruction comprises a desensitization identifier of the credit assessment object. And determining a global credit score of the credit assessment object based on the local credit score fed back by each assessment participation node and the weight set corresponding to the credit assessment request, and sending the global credit score to the credit assessment node. Through the method, the credit assessment coverage data is improved, and the credit assessment is carried out in time, so that the personal credit risk assessment is accurately completed.

The invention discloses a method for reducing line loss and improving power supply reliability based on the Internet of Things, and the method comprises the steps: carrying out the full-dimension load and line state monitoring: deploying an Internet of Things sensor, constructing an end-to-end monitoring network, and collecting key parameters in real time; a low-delay and wide-coverage data channel is constructed; a layered communication architecture is adopted, and efficient data transmission is realized; the real-time analysis and intelligent decision engine is used for constructing a load-line-equipment three-dimensional data model based on a cloud end and an edge platform, and realizing line loss real-time diagnosis, load prediction, situation awareness and rapid fault positioning; dynamic optimization and self-healing control: based on a data layer analysis result, source-network-load coordinated regulation and control are realized through an Internet of Things terminal, line loss is reduced, and stable power supply is guaranteed; user interaction and global optimization: realizing power grid-user interaction and peak load shifting through a user-side Internet of Things terminal to reduce the pressure of a power system; the system has the advantages of being capable of reducing line loss, guaranteeing power supply reliability, having various functions and being good in comprehensive application effect.

The invention discloses a cloud management and intelligent distribution method for classroom teaching resources, and relates to the technical field of cloud computing software. The classroom teaching resource cloud management and intelligent distribution method comprises the steps that S1, multi-source teaching resource data and auxiliary distribution data are acquired and preprocessed, and a knowledge content database is constructed; s2, performing semantic fusion analysis through text semantic association, structural consistency and professional term coverage data; s3, carrying out dependency evaluation by fusing pre-association, knowledge co-occurrence, sequence association and semantic fusion data; s4, performing resource adaptability distribution analysis through the maximum knowledge dependence value in combination with the learning state data and the historical feedback data; and S5, evaluating the teaching resource quality by collecting classroom feedback, teacher evaluation and resource use data, and implementing content optimization. The problems of semantic distortion, path breakage, distribution mismatching and resource updating inconsistency in the teaching resource data fusion and intelligent resource distribution process are solved.

The invention belongs to the field of software testing and defect detection, focuses on reliability verification of a physical simulation engine, is suitable for scenes depending on physical simulation, such as robot simulation, automatic driving testing, unmanned aerial vehicle control, education and scientific research, and particularly relates to a variation-based physical simulation engine defect detection method. Potential defects of core modules of collision detection, mechanical calculation, dynamics and the like are efficiently found through a variation test method. According to the method, a feature library is constructed through static library API analysis and AST / IR code analysis, test code expansion is performed by utilizing a large model, a test driver adaptive to a specific data type is generated, a physical semantic constraint mutation seed is combined, a test is executed through libFuzzer, defect and coverage rate data are analyzed, a use case selection strategy is optimized, and the test efficiency is improved. Defects of core modules such as collision detection and dynamic solution are efficiently detected, and the test pertinence and efficiency are improved.

The invention provides an automobile electronic control unit fuzzy testing method based on partial code coverage rate feedback and a computer, and belongs to the technical field of automobile electronic control unit code testing. The computer performs static analysis on source codes of the automobile electronic control unit, identifies inevitable execution blocks and conditional execution blocks, performs selective instrumentation on the conditional execution blocks, and inserts coverage rate recording instructions of the conditional execution blocks. And the computer source code is loaded into the automobile electronic control unit, and a test input signal is generated through the fuzzy test engine and is injected into the automobile electronic control unit. In the process of executing the program by the automobile electronic control unit, recording the coverage condition of the condition execution block to a bitmap in the memory; the computer reads the coverage rate data of the condition execution block through the debugger every time a complete execution cycle is completed; and the fuzzy test engine adjusts the input generation strategy according to the coverage rate data feedback of the condition execution block and tests again. According to the method, the automobile electronic control unit source code fuzzy test coverage condition is efficiently collected.

The invention discloses an automobile interior and exterior decoration product size measurement method based on automatic scanning, and belongs to the field of automobile part detection, and the method comprises the following steps: carrying out the non-contact comprehensive scanning of an automobile interior and exterior decoration product through a 3D automatic scanner, and obtaining high-precision point cloud data; preprocessing the point cloud data, including denoising, splicing and three-dimensional reconstruction, and generating a product digital model corresponding to the real object; performing automatic alignment and size comparison on the product digital model and a preset CAD design model, and calculating a deviation error of each feature size; and performing automatic qualification judgment on the deviation error based on a preset tolerance standard, and generating a detection report containing an error analysis result and a judgment conclusion. According to the automobile interior and exterior decoration product size measurement method based on automatic scanning, full-coverage data acquisition can be completed in a short time through 3D automatic scanning, the measurement efficiency is improved, the dependence on the experience of measurement personnel is reduced, and high-precision measurement of the size of the automobile interior decoration product is realized.

A method for delineating an ore body of deep-sea polymetallic nodules based on coverage data includes steps as follows. Ore body data of the deep-sea polymetallic nodules is obtained, the ore body data includes: mining site production scale parameters, mining system parameters, and ore body geological characteristic parameters. A boundary coverage rate and a cumulative weighted average coverage rate are calculated based on the mining site production scale parameters, the mining system parameters, and the ore body geological characteristic parameters. The ore body is delineated, based on the boundary coverage and the cumulative weighted average coverage, through a principle of ore body boundary range delineation to obtain an ore body range. The method delineates ore body of nodule with proper geological continuity based on abundance data. It can be directly applied to deep-sea polymetallic nodule mining, solving the problems existing in the delineation of ore body of deep-sea polymetallic nodule.

The invention discloses a landslide maneuverability confirmation method and system based on an adaptive difference model, and relates to the technical field of data processing, and the method comprises the steps: obtaining a sub-slope region, and obtaining a vegetation coverage data sequence; obtaining a difference index, obtaining a first to-be-processed data sequence, obtaining a second to-be-processed data sequence, obtaining a difference sequence of the first to-be-processed data sequence, obtaining a first fluctuation index, and if the first fluctuation index exceeds a third preset threshold value, taking a sub-slope region corresponding to the first to-be-processed data sequence as a sliding source region boundary region; acquiring a difference sequence of the second to-be-processed data sequence, acquiring a second fluctuation index, and if the second fluctuation index exceeds a fourth preset threshold value, taking a sub-slope region corresponding to the second to-be-processed data sequence as a landslide region boundary region; and obtaining a target sliding source area, a target landslide area and an area proportion. The method has the advantages of self-adaptive difference distinguishing, stable and accurate boundary and dynamic quantization.

The invention discloses an accumulated snow coverage analysis method and system and a medium, and the method comprises the steps: obtaining a plurality of pieces of to-be-processed satellite data of a to-be-analyzed region; performing feature extraction on the to-be-processed satellite data to obtain multi-dimensional feature data of each preset pixel; analyzing the multi-dimensional feature data, and determining a first accumulated snow identification result; respectively determining a plurality of target preset pixels geographically covering each preset geographic grid; carrying out statistics on distribution of the first accumulated snow identification results of a plurality of target preset pixels in each preset geographic grid, and determining a state statistical index; constructing a time data sequence of a preset geographic grid; analyzing the time data sequence of each preset geographic grid, and determining a second accumulated snow identification result of each preset geographic grid; and generating an accumulated snow coverage data set of the to-be-analyzed area based on the second accumulated snow identification result. The precision of the accumulated snow coverage data is improved.

The invention provides a global biodiversity hot spot area threat condition remote sensing monitoring method and system, and relates to the technical field of ecological environment monitoring, spatial analysis and remote sensing and information processing, and the method comprises the steps: obtaining multi-temporal global land coverage data and auxiliary GIS data of a biodiversity hot spot area, and carrying out the preprocessing; extracting forest coverage layers of a reference period and a monitoring period from global land coverage data, and extracting pixels converted from a forest to a non-forest through a layer difference method to generate a forest loss layer; based on the forest loss map layer and the preprocessed auxiliary GIS data, calculating various ecological pressure indexes including a forest loss rate, a protection failure rate and a population pressure index, and performing normalization; and calculating a comprehensive threat index based on each ecological pressure index, and determining an ecological threat level. According to the method, automatic identification, quantitative evaluation and grading of the ecological threats of the hot spot region are realized, and technical support is provided for global ecological protection planning and management.

The invention provides an automatic calculation method, system, equipment and program product for incremental code coverage rate, which are applied to the field of software testing, and the method comprises the following steps: receiving a code version change event, collecting and merging binary coverage rate data, obtaining an incremental code change set, and generating a structured coverage rate report. According to the scheme, the incremental code coverage rate can be accurately calculated, and the code quality measurement efficiency is improved.

The invention discloses a method for predicting the coverage degree of an H ion negative electrode in a Zn aqueous battery, and relates to the technical field of surface catalysis. In order to solve the defect that in the prior art, it is difficult to accurately predict the coverage degree of H ions on the surface of a Zn negative electrode on a multi-scale level, the technical scheme provided by the invention comprises the steps that a three-dimensional atom structure model of H atoms and a Zn electrode adsorption surface is constructed, formation energy and adsorption energy of the H ions and water molecules are calculated, and a reaction potential energy surface is established; constructing a reaction path and an electron transfer behavior, defining potential related parameters, and outputting reaction rate, current density and coverage data; establishing a phase field dilute material transfer model containing temperature, pH and pressure parameters, and completing material migration and charge distribution calculation; interface physical field parameters are fed back to the microdynamics model to form microcosmic-macroscopic bidirectional data interaction and realize self-consistent convergence; and outputting a coupling model result to obtain multi-scale prediction data. The method is suitable for active site identification and performance prediction in electro-catalytic reaction.

The invention discloses a method, a device, equipment and a medium for dynamically generating a smoking test case set, and relates to the technical field of chip verification, coverage rate data is collected, code change data is obtained according to a code version, priority index data is determined according to the coverage rate data and the coverage rate data corresponding to the code change data, and a smoking test case set is dynamically generated according to the priority index data. And screening the test cases in combination with weight coefficients determined by different change types determined by the priority index data so as to dynamically generate a smoking test case set. Therefore, the method replaces a static use case set, instead, the use case set is adjusted in real time according to code change and coverage rate change, priority indexes are balanced through a priority algorithm, few use cases are focused, high coverage is achieved, and efficiency is improved.

The invention relates to the technical field of electronic design automation, in particular to a method for collecting flipping coverage rate data during simulation, electronic equipment and a storage medium, and the method comprises the steps: registering a value change callback function for each instantiated flipping variable; when the flip variable is the scalar variable, the monitoring object of the value change callback function is the scalar variable; when the flip variable is an aggregation variable, the monitoring object of the value change callback function is each sub-variable; during simulation, if the value of the monitoring object in the flip variable changes, collecting coverage state data of the target monitoring object through a value change callback function, and updating a target bit corresponding to the target monitoring object in the coverage state bits according to the coverage state data; and when all the coverage data of the coverage state bit are valid data, deleting the value change callback function registered for the target flip variable, thereby improving the simulation efficiency and the resource utilization rate.

The invention relates to the technical field of information engineering knowledge graph construction, in particular to a supervision knowledge graph dynamic modeling method based on multi-source heterogeneous data fusion, and the method comprises the steps: designing a four-dimensional knowledge graph modeling framework, and combining the entity alignment of a graph neural network, the relation extraction of remote supervision and the attribute processing of weight fusion. A dynamic evolution and cross-source consistent knowledge network is constructed, virtual features are generated through a virtual feature compensation mechanism (historical event retrieval and multi-dimensional feature weighted fusion) for a multi-modal data missing scene and mapped to a graph, data are effectively filled, the problem of incomplete knowledge coverage in a complex engineering scene is solved, a compliance entropy evaluation model is introduced, and the knowledge coverage is evaluated. The compliance state of the knowledge graph is quantitatively supervised from the three dimensions of rule coverage rate, data consistency and tracing integrity, and the hysteresis and subjectivity limitation of traditional manual compliance check is broken through.

The invention relates to the technical field of automatic logistics transportation, and discloses an automatic transportation OHT path selection method, which comprises the following steps: acquiring OHT real-time state and position data, track network environment parameters and the number of OHT in each area of a wafer factory; the historical OHT traffic data is preprocessed; generating a path set from the starting point to the ending point based on the map data structure; calculating dynamic weight values of the paths and sorting the dynamic weight values; performing optimization decision on the path based on convex optimization, a queuing theory and LSTM prediction; and determining a final execution path according to the optimization decision and issuing the final execution path to the OHT. According to the automatic conveying OHT path selection method, through multi-process operation, coverage data acquisition, preprocessing, path set generation, weight calculation and the like, a path which accords with reality and has perspectiveness is determined, meanwhile, path planning is dynamically adjusted through real-time monitoring and closed-loop feedback optimization, and then the conveying efficiency is improved. The problem of low carrying efficiency in a traditional path selection method is solved.

The invention discloses a WeChat applet JS-SDK code defect detection method, system and device and a medium, and the method specifically comprises the steps: based on an instrumentation framework, carrying out API calling through a wx proxy object of a WeChat applet, recording an API calling path, a parameter combination and an execution state, and generating API-level fine-grained coverage rate data; the API-level fine-grained coverage rate data, API calling tracking data and code version library change records are stored in an associated mode, and a time-space associated data warehouse is constructed; based on the data warehouse, modeling the historical coverage rate sequence by using an LSTM neural network, predicting the risk level of uncovered codes, and generating targeted test case suggestions; based on the data warehouse, uncovered codes and recent code changes are matched through an Szz algorithm, potential defect positions are positioned, and defect confidence is marked. The WeChat applet JS-SDK code quality guarantee method provides comprehensive and accurate support for WeChat applet JS-SDK code quality guarantee, and the development efficiency and the code reliability are improved.

A method and a system for efficient callback functionality can utilize signal coverage data. For example, a computer-implemented method can be configured to allow an emergency call taker to perform successful callbacks in case of abandoned emergency calls due to signal coverage and / or antenna overload issues in a location.

The application discloses a weak coverage area grid clustering method and device, and the method comprises the following steps: performing slicing processing on a raster map to obtain a plurality of map slices; calculating the weak coverage probability of each map slice; screening the map slices to be clustered from the plurality of map slices according to the weak coverage probabilities of the plurality of map slices, performing clustering processing on the grids in the map slices to be clustered to obtain a weak coverage clustering cluster; collecting the update coverage data corresponding to the plurality of map slices, and updating the raster map according to the update coverage data and the weak coverage clustering cluster. The application realizes the management and processing of different slices by screening the map slices to be clustered, and does not need to perform complete traversal clustering and updating on the entire raster map, thereby saving the computing resource, effectively improving the update speed of the raster map, and solving the problems that the current clustering operation requires a large computing power and the real-time update map operation consumes a large amount of resources.

This disclosure relates to the field of robotics technology, providing a method for handling missed cleaning areas, a cleaning robot, a system for handling missed cleaning areas, a computer-readable storage medium, and an electronic device. The method includes: identifying missed cleaning areas within an explored area based on actual cleaning coverage data and historical cleaning records during the cleaning task execution process; and generating the cause of the missed cleaning area based on environmental perception data during the cleaning task execution process. This disclosure can automatically identify missed cleaning areas and accurately analyze their causes, significantly reducing the burden of manual troubleshooting for users.

The invention relates to a leaf area index time sequence processing method, which comprises the following steps of: inputting a time sequence remote sensing image and suburb forest and economic forest classification data of the same region; calculating a normalized differential vegetation index of the research area and carrying out time sequence sorting; calculating vegetation coverage data of the research area and carrying out time sequence sorting; synthesizing to obtain monthly FVC time sequence data of the suburb forest region and the economic forest region; calculating a suburb forest leaf area index LAI in the research area and performing time sequence sorting; calculating the economic forest leaf area index LAI of the research area and performing time sequence sorting; performing seasonal decomposition on the suburb forest time sequence data after adaptive filtering; performing seasonal decomposition on the economic forest time series data after adaptive filtering; merging the suburb forest time sequence data and the economic forest time sequence data; and outputting to obtain final optimized data. The invention further relates to a leaf area index time sequence processing system. According to the invention, a purification LAI time sequence product which clearly represents long-term trend, mutation and gradual change signals of respective vegetation canopy structures can be output.

Disclosed here are methods, systems, and apparatuses for optimizing in-building network coverage through aggregation of usage data, network data, and other performance metrics and geospatial analysis employed to map network coverage data onto a geographic grid, facilitating spatial visualization of performance. The network coverage data is mapped to the buildings data to create a spatial visualization. A model is then applied to the network coverage data and the spatial visualization to identify buildings with a network coverage score below a threshold, and an appropriate action is performed based on the identification.

The invention discloses a test case determination method and device and electronic equipment. The method comprises the steps that a to-be-verified target code unit is determined; the target code unit represents a code unit corresponding to the to-be-verified function point in the algorithm model; obtaining a coverage rate database, wherein the coverage rate database represents the coverage degree of each test case in the test case library on a preset granularity code unit in the algorithm model; and querying in a coverage rate database based on the target code unit to obtain a test case covering the target code unit as a target test case.

This technology relates to a system for reviewing the feasibility of requests to modify telecommunications network access nodes. The system reviews accompanying data presented for the requested change by pre-processing data. The pre-processing includes calculating, based on the accompanying data of the request, population data, coverage data, and subscriber data. Based on the population data, the coverage data, and the subscriber data, the system may generate a justification package and transmit it to a decision center, a software program designed to assess the desirability of changes to telecommunications network access nodes. The decision center responds to the request with an approval or rejection decision. The system may receive further requests to modify the telecommunications network access node following the approval or rejection of the initial request.

The invention discloses a software testing method and device, a medium and a product, and relates to the technical field of software test.The software testing method includes the steps that coverage rate data of unit testing, integration testing and system testing of target software are collected through a code coverage rate analysis tool, and the coverage rate data are converted into target text files; the coverage rate data comprises execution times and coverage rates of the codes; storing each target text file in a corresponding target directory, and reading and analyzing the target text file in each target directory to obtain corresponding analyzed data; the analyzed data comprises a total row number, a total branch number, a total function number, a total coverage row number, a total coverage branch number and a total coverage function number; and merging and storing the analyzed data into a preset nested dictionary, traversing the preset nested dictionary to determine the code coverage rate of the target software based on the traversed analyzed data, and determining the software defect of the target software by using the code coverage rate. The quality and stability of software can be improved through testing.

The application relates to the technical field of intelligent robot inspection, and discloses a somatic intelligent AI inspection method based on digital twinning, wherein the somatic intelligent AI inspection method based on digital twinning comprises the following steps: a dynamic attention multi-layer feature extraction network is used to analyze multispectral images collected by a robot-mounted sensor to generate a real-time distribution diagram of industrial facility abnormal coverage; a space-time sequence contrast learning model is used to analyze historical abnormal coverage data to generate an abnormal coverage trend prediction; a physically constrained neural differential equation model is used to analyze an abnormal coverage evolution process to generate an accurate abnormal evolution prediction result; a multi-objective optimization algorithm is used to generate an optimal inspection path; a digital twinning system is dynamically updated, and an industrial facility maintenance optimization suggestion is generated; and through the dynamic attention multi-layer feature extraction network and a light condition self-adaptive enhancement algorithm, the detection difficulty in a strong light and high reflection environment is effectively solved.

The invention relates to the field of unmanned aerial vehicle intelligent scheduling, and discloses a multi-unmanned aerial vehicle cooperative full-coverage path planning optimization method and system, and the method comprises the steps: carrying out the continuous grid scanning of an inspection region based on the local terrain complexity, the obstacle density and the unmanned aerial vehicle sensing coverage radius; the real-time electric quantity, the load capacity, the speed limitation and the communication link state of each unmanned aerial vehicle are evaluated, and a cooperative capacity matrix is constructed; based on a variable-size operation unit and a matching map, introducing an adaptive collaborative optimization model, and predicting track conflict, coverage redundancy and energy consumption deviation through multiple factors; the coverage information and the abnormal state of the unmanned aerial vehicle are collected in real time in the inspection process, and when missing or repeated coverage is found, incremental replanning is executed for the affected local operation unit; and based on the coverage data and energy consumption statistics after each round of inspection is completed, calculating a coverage efficiency index and omission risk distribution in combination with real-time and accumulated data. The method has the advantages of improving the inspection efficiency and reducing the omission risk.