175 results about "High coverage" patented technology

The invention provides a test case generation and script optimization method and device based on machine learning, and the method comprises the steps: carrying out the training of a large model based on a Transform architecture through a public test case data set, calling the large model to generate a plurality of test cases meeting the business demands, recognizing the key operation steps in the test cases, and carrying out the script optimization of the test cases. Inserting check points at corresponding positions, converting the test script into an automatic test script described by a script language, and optimizing an execution sequence of the test script through a graph neural network; dynamically adjusting the structure of the test script through a deep reinforcement learning algorithm, generating a simulation test environment in combination with a GAN (Generative Adversarial Network), and verifying the test script. According to the method, the test case with high coverage rate and high quality can be automatically generated, the manual compiling cost is reduced, the automatic test script highly matched with the test case can be dynamically generated, and the execution efficiency is improved by optimizing the structure.

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 provides a chemical industrial park unmanned aerial vehicle group patrol path optimization method, device and equipment, and relates to the technical field of unmanned aerial vehicle patrol, and the method comprises the steps: obtaining the environment data of a target chemical industrial park, and the attributes and initial patrol paths of all unmanned aerial vehicles; aiming at any unmanned aerial vehicle, acquiring each patrol position on the initial patrol path and a real-time monitoring value of the corresponding patrol position; for any patrol target in charge of the unmanned aerial vehicle, obtaining the weight when the unmanned aerial vehicle arrives at the patrol target; inputting each patrol position and the corresponding real-time monitoring value, the target position and weight of the patrol target, the environment data and the initial patrol path into a pre-constructed multi-target optimization model, and calculating a score of the initial patrol path; according to the weight, the target position, the environment data, the attribute and the initial patrol path and the position of each unmanned aerial vehicle, determining an optimal patrol path of the unmanned aerial vehicle by adopting dynamic neighborhood search; according to the method, the optimal patrol path with high efficiency, safety, high quality and high coverage rate can be generated.

The invention relates to the technical field of three-dimensional model processing, in particular to a solar wing battery selecting and matching method and system based on three-dimensional layout. The method comprises the following steps: acquiring three-dimensional data of a solar wing, and constructing a three-dimensional substrate model according to the three-dimensional data of the solar wing to obtain a three-dimensional model of the solar wing; performing structure-driven spreading strategy simulation on the three-dimensional model of the solar wing to obtain fixed simulation data, and performing fixed strategy simulation on the three-dimensional model of the solar wing to generate a disturbance type layout scheme to obtain random simulation data; performing regional structure domain analysis on the fixed simulation data and the random simulation data to obtain regional structure domain data, and performing optimal layout sorting on the regional structure domain data to obtain layout sorting data; and performing two-dimensional drawing export on the layout sorting data to obtain solar wing battery matching data. According to the method, the diversity of the scheme can be effectively expanded, the local adaptability is improved, and the high coverage rate and the optimal sorting output are realized under the condition of ensuring the structural constraint.

The invention discloses a decision planning system-oriented simulation test scene automatic generation method. The method comprises the steps of scene modeling: constructing a scene model by using a deep learning model; constraint generation: based on an output result of the scene model, utilizing a reinforcement learning model to generate a constraint condition; performing optimization search: based on the scene model and the constraint conditions, generating scene parameters meeting constraints by adopting a Bayesian optimization algorithm; and scene evaluation: evaluating the system performance by using the deep reinforcement learning model. According to the simulation test scene automatic generation method facing the decision planning system, manual intervention is reduced through an automatic method, and the scene generation efficiency is improved; diversified and high-coverage test scenes are generated, the scene diversity is enhanced, and the robustness of the system is comprehensively tested; constraint processing is optimized by efficiently processing complex constraint conditions, and it is ensured that a generated scene meets system requirements; and comprehensive system performance evaluation is provided, multi-dimensional evaluation is realized, and the performance of the system in different scenes is reflected.

Provided is a causal relationship graph generation device with which it is possible to easily create a causal relationship graph with high coverage. On the basis of a detection parameter, which is data used in order to detect an incident occurring in a system, and a data flow indicating the flow of data used in the system, a related element extraction unit 13 identifies a related element, which is an element affecting the detection parameter, among elements on the data flow. A graph generation unit 14 identifies a related event, which is an event causing an incident, on the basis of system information and the related element identified by the related element extraction unit 13, and generates a causal relationship graph on the basis of the related event.

The invention discloses a software defect positioning method and system based on multi-stream model fusion. The method comprises the following steps: firstly, filtering test cases with relatively high coverage rate by adopting a test case reduction strategy, and weighting the residual test cases by utilizing a test case weighting strategy so as to reflect the capability of the test cases for revealing defects; frequency spectrum features, variation features, local semantic features and global structure features are extracted, the frequency spectrum features and the variation features are calculated through a weighted suspicious degree formula, and the local semantic features and the global structure features are obtained through a deep learning technology; and finally, fusing the four types of features, and inputting the fused features into a defect positioning predictor trained by a multi-layer perceptron to obtain a suspicious degree score of each code statement, so that suspected defect statements are screened out by taking the suspicious degree scores as positive correlation indexes of the defect statements, and software defect positioning is realized. According to the method, the code defect mode can be effectively disclosed, so that the accuracy of software defect positioning is improved.

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 belongs to the field of software testing in software engineering, and particularly relates to a test case sorting method based on a multi-arm bandit algorithm, which can be used for optimizing the execution sequence of test cases and improving the fault detection efficiency. According to the method, the execution sequence of the test cases can be dynamically optimized, and the fault detection efficiency is remarkably improved. Through combination of coverage rate information and fault probability prediction, the test cases with high fault probability and high coverage rate can be executed preferentially, and waste of test resources is reduced. In addition, the method has high expandability and can adapt to industrial software systems of different scales and complexity.

The invention discloses an unmanned aerial vehicle autonomous cruise and obstacle avoidance method and system for a dynamic no-fly zone. Relates to the technical field of unmanned aerial vehicle autonomous navigation and path planning. The method comprises the following steps: issuing and keeping a no-fly zone set static in a task initialization stage; fusing the multi-source sensing data through a layered SLAM mapping module to generate an occupied grid map; performing global path planning by adopting an improved BFS algorithm and a weighted greedy strategy based on a map, and generating a patrol sequence covering reachable points; compressing and smoothing the spliced path to generate a final cruise trajectory; and triggering local trajectory re-planning for sudden obstacles in a non-no-fly zone based on SLAM perception in flight. According to the invention, autonomous cruise and dynamic obstacle avoidance with high coverage rate and low redundancy are realized under the condition of strictly following the constraint of the static no-fly zone.

The invention discloses an SAR satellite strip mode task planning method, and aims to maximize the area coverage rate. According to the method, basic data containing time sequence geometric coverage primitives are obtained, and candidate planning schemes containing mixed parameters are initialized. During iterative optimization, an imaging interval is determined according to planning parameters, corresponding geometric primitives are identified, geometric merging calculation is executed to determine a planned coverage area, the area coverage performance is evaluated in combination with load constraint, and the parameters are updated by using an optimization algorithm. And outputting an optimal scheme after iteration. According to the method, through accurate geometric coverage calculation and constraint processing, the problems of inaccurate coverage estimation, incomplete constraint consideration and low planning efficiency are solved, and a feasible planning result with higher coverage rate and better performance can be quickly generated.

According to the gluing track design method, the storage medium and the electronic equipment, the to-be-glued area is divided into the multiple period design domains, after the gluing starting position is selected, the multiple gluing tracks in each period design domain are planned according to the genetic optimization algorithm, and according to the fact that the coverage rate corresponding to the gluing result is not smaller than the target gluing coverage rate, the gluing track is designed. Under the conditions that the gluing thickness corresponding to the simulated gluing result is consistent with the target gluing thickness and the gluing amount corresponding to the simulated gluing result does not exceed the target gluing amount, the optimal gluing track is selected from the multiple gluing tracks to serve as the final gluing track. According to the scheme, based on a genetic optimization algorithm framework, a gluing track parameterization expression method of a multi-cycle design domain is established, gene crossover and gene variation mechanisms are improved, and a gluing track planning method with the coverage rate, the gluing thickness and the gluing amount meeting target requirements is provided. According to the scheme, the gluing track meeting the requirements for the coverage rate and the glue amount can be obtained, and the advantages of being high in coverage rate and low in glue amount are achieved.

The invention discloses a forestry ground multi-robot cooperative full-coverage path planning method and device based on a diffusion model, electronic equipment and a storage medium. The method comprises the following steps: constructing an enhanced environment model containing passing cost and reachability probability through multi-source sensor fusion; based on the model, generating a global path probability field with coherence and environmental adaptability by using a diffusion model; further realizing multi-robot self-adaptive task region division through a path flow field gradient; a local diffusion replanning mechanism is introduced for dynamic obstacles to carry out rapid path repair; and performing multi-objective optimization on the path in combination with a robot center Euclidean symbol distance field, and outputting an executable path meeting safety, smoothness and kinematics constraints. According to the method, through closed-loop design of perception, modeling, generation, division, re-planning and optimization, high-coverage, high-collaboration and high-robustness autonomous inspection of multiple robots in a complex forest region environment is realized, and reliable technical support is provided for smart forestry.

The invention relates to the technical field of wireless sensor networks, in particular to a heterogeneous wireless sensor network coverage method for a mountain new energy construction site, which comprises the following steps of: constructing a three-dimensional mountain monitoring area, inputting related parameters and establishing a multi-target optimization model taking the non-coverage rate, the reciprocal of the connectivity rate and the minimum total energy consumption as targets; initializing a dung beetle population, dividing the dung beetle population into four classes, obtaining an initial coverage scheme, and screening a non-dominated coverage scheme solution set for storage; iteratively updating the positions of various types of dung beetles based on a multi-target dung beetle optimization algorithm; the current coverage scheme and the archive set are combined, the archive set is updated after non-dominated sorting, and dense solutions are discarded to guarantee diversity when the scale is over-scale; and outputting a solution set after the maximum number of iterations is reached, and selecting a target scheme to complete node deployment. The method is adaptive to complex mountain scenes, network coverage and communication quality are improved, energy consumption is reduced, local optimum is avoided, and mountain monitoring effects of high coverage, low energy consumption and strong adaptation are achieved.

The invention provides a test case determination method and device, electronic equipment and a storage medium, and the test case determination method comprises the steps: determining a multi-dimensional feature vector of a test scene of an automatic parking function; determining the similarity between the test scenes based on the multi-dimensional feature vectors, and generating a similarity matrix based on the similarity between the test scenes; performing clustering analysis on all the test scenes based on the similarity matrix so as to classify the test scenes of which the similarity meets a preset clustering condition into the same cluster; and selecting a representative test scene from each cluster, and performing duplicate removal on the representative test scene to obtain a test case set. According to the method and the device, the test case with high coverage rate can be automatically and efficiently determined, and the redundancy of a test scene is reduced.

This invention relates to the field of strategic planning technology, and discloses a strategy generation method and system based on anchor bolt mesh installation. The method includes: acquiring all anchor bolt positions and mesh sizes within the tunnel, and correcting the mesh sizes; digitally twinning the anchor bolt positions in a three-dimensional coordinate system to construct a multi-layered mesh digital twin model; and performing multi-objective strategy optimization on the multi-layered mesh digital twin model to generate a mesh installation strategy on the anchor bolts. This invention can automatically generate mesh installation schemes with high coverage, low loss, and strong stability, reducing manual intervention, material waste and rework rates, effectively improving construction quality and automation levels, and has significant engineering application value and promising prospects for wider application.

The invention discloses a file processing method and device, a coverage rate collection method and device, electronic equipment and a storage medium. The file processing method comprises the following steps: in response to a packaging instruction for a service source code of a target service, if it is determined that the packaging instruction comprises a target parameter, importing a dependent packet for the target service; the target parameter is used for indicating that the target service has a coverage rate acquisition requirement; the dependency package comprises a file for realizing code coverage rate collection on the target service; in response to successful import of the dependency package, processing the dependency package based on the service source code to obtain a coverage rate toolkit; and based on the business source code packaging result of the business source code and the coverage rate toolkit, determining a target installation package for the target business. According to the method, the deployment efficiency of the code coverage rate collection function is improved, the deployment cost of the code coverage rate collection function is reduced, and then the purposes of improving the coverage rate collection efficiency and reducing the coverage rate collection cost are achieved.

The application relates to a room division covering system and method based on frequency shift MIMO technology, which comprises a signal source access layer, a frequency shift MIMO core processing layer and a distributed covering layer. The signal source access layer is used for acquiring multi-system signal sources; the frequency shift MIMO core processing layer is connected with the signal source access layer and the distributed covering layer respectively, is used for receiving the multi-system signal sources and the real-time feedback of channel parameters of indoor areas of the distributed covering layer, performing cooperative detection of channels and scenes, combining frequency shift MIMO technology to perform cooperative processing, and obtaining frequency shift-MIMO cooperative signals; and the distributed covering layer is used for receiving the frequency shift-MIMO cooperative signals, forming a radio frequency covering field based on frequency shift MIMO technology, accessing adaptive terminals, and collecting real-time channel parameters of indoor areas. Compared with the prior art, the application has the advantages of high covering rate and adaptive environmental change.

The invention provides a similar data detection method and device, and the method comprises the steps: extracting a multi-level hyper-feature of a target data block, the multi-level hyper-feature comprises a plurality of levels of hyper-features, and the similarity detection threshold value of the high-level hyper-feature is higher than the similarity detection threshold value of the low-level hyper-feature; based on the multi-level hyper-features, similarity matching is carried out from a hyper-feature data set to obtain a matching result, and the hyper-feature data set comprises the multi-level hyper-features corresponding to the data blocks in the data block set; and based on a matching result, determining a similar data block corresponding to the target data block. According to the similar data detection method provided by the invention, similar matching is carried out through the multi-level hyper-features with different similar matching thresholds, the coverage rate and the accuracy rate of similar data matching are considered, and high coverage rate and high accuracy rate of similar data matching are realized.

Provided is a multilayer ceramic capacitor provided with an internal electrode capable of maintaining a relatively high coverage rate even when the multilayer ceramic capacitor is thinned. A laminated ceramic capacitor (1) is provided with a laminated body (2) having: a plurality of laminated dielectric layers (3) containing a ceramic; and a plurality of internal electrodes (4, 5) disposed along each of a plurality of interfaces between the dielectric layers (3). When the conductive metal or the alloy containing the conductive metal is represented by X, the internal electrodes (4, 5) contain a conductive component and a ceramic component, the conductive component contains X, and the ceramic component contains XTiO3. Preferably, X is one selected from nickel, copper, silver and a silver-palladium alloy.

Providing a representative dataset from an initial dataset by accessing a dataset associated with a machine learning model, receiving input parameters associated with the representative dataset selection, the input parameters including an evaluation metric, determining a density of a plurality of datapoints associated with the dataset, training a first iteration of a machine learning model using a first data point selected according to the density, determining a first value of the evaluation metric for the first iteration of the machine learning model, generating a representative subset based on the first value of the evaluation metric value, and providing the representative dataset and a final machine learning model trained using the representative dataset.

The purpose of the present invention is to provide a composite film having a high coverage of a nanocrystalline plate and a high amount of light absorption per unit thickness. A composite film (10) including a nanocrystalline plate (11) having a composite layer structure in which a first layer containing a cation A to which ligands coordinate and a second layer containing a cation B and an anion X are alternately stacked, wherein the aspect ratio (L / S or S / L) that is a rectangular shape feature amount in a direction intersecting the stacking direction of the composite layer structure is 0.2-5, when the thickness of the nanocrystalline plate is denoted by t and the length of the short axis intersecting the stacking direction of the nanocrystalline plate is denoted by S, t and S satisfies S / t ≥ 3, and a variance σn of the number of stacked layers in the nanocrystalline plate is 0.7 or less.

The invention provides a method and a device for inspecting a photovoltaic panel by an unmanned aerial vehicle, and the method for inspecting the photovoltaic panel by the unmanned aerial vehicle comprises the steps: S1, obtaining a planar grid map which comprises a plurality of first grids corresponding to the photovoltaic panel; and S2, a particle swarm is generated based on a particle swarm optimization algorithm, the particle swarm comprises N particles, each particle traverses all the first grids, N traversal paths connected with all the first grids are obtained respectively, and the lengths of the N traversal paths are compared, so that the shortest path is obtained, the unmanned aerial vehicle performs routing inspection based on the shortest path, and N is greater than or equal to 2. According to the method for polling the photovoltaic panel by the unmanned aerial vehicle, the polling efficiency of the photovoltaic panel by the unmanned aerial vehicle is high, and the coverage rate is high.

The utility model relates to the technical field of time sequence control mainboard testing devices, in particular to a testing device of an OLED time sequence control mainboard, which comprises an OLED time sequence control mainboard main body, a signal input interface is arranged on the upper surface of the OLED time sequence control mainboard main body, a connecting area is arranged on the upper surface of the OLED time sequence control mainboard main body, and the signal input interface is connected with the connecting area. A first golden finger is fixedly arranged in the connecting area, a flexible printed circuit board is arranged above the OLED time sequence control mainboard body, and a second golden finger is fixedly arranged on the bottom face of the flexible printed circuit board. The OLED time sequence control mainboard testing device can be suitable for testing OLED time sequence control mainboards of different models, the design method of the device can be completely covered, meanwhile, on-load connection testing of the OLED time sequence control mainboards and full-function testing of products of the OLED time sequence control mainboards can be completed, high-coverage testing of a network is achieved, and the testing efficiency is improved. And traceless, damage-free, batch and efficient testing can be realized during testing.

The invention discloses a hierarchical reinforcement learning-based skill consecutive recruitment construction method and a terminal. The method comprises the following steps of: modeling state data of a virtual environment by using a depth time sequence modeling algorithm, and generating a sub-target sequence according to the state data; generating a first consecutive call sequence based on the sub-target sequence, identifying illegal operations and potential risks in the first consecutive call sequence, and optimizing to generate a second consecutive call sequence; and with the consecutive call effect, the resource consumption and the consecutive call stability as targets, optimizing the second consecutive call sequence by using a reward function, and constructing and generating an optimal skill consecutive call sequence. According to the method, the virtual environment is comprehensively modeled by using the depth time sequence modeling algorithm, the legality and stability of the consecutive call are verified and optimized through the rule constraint and decision search algorithm, illegal operation and potential risks in skill consecutive call are effectively avoided, and the dynamic adaptability of consecutive call construction is improved, so that high coverage rate and high efficiency are realized. And the skill continuous call test efficiency is effectively improved.

The application provides a full-area coverage path planning method and device for a mowing robot, a terminal and a medium. The method comprises the following steps: abstracting an environment map by setting a virtual boundary line of one or more target mowing areas; determining a long-axis direction of a bow shape for each target mowing area and rotating each target mowing area; dividing the one or more target mowing areas into one or more sub-areas based on the boundary points of the rotated target mowing areas; performing path planning for each target mowing area based on the long-axis direction of the bow shape of the target mowing area; and connecting the bow-shaped paths of the target mowing areas based on a navfn algorithm to obtain a full-area coverage path corresponding to the environment map. The application can realize full-area coverage path planning, has a high coverage rate even for a complex mowing area, has a low repetition rate, and greatly increases the path planning efficiency of the mowing robot.

The present invention relates to the technical field of salt crust detection, and discloses a method and system for detecting soil salt crust in coastal areas. The method comprises: obtaining the soil surface albedo of a target detection area to determine whether the target detection area is an area with high coverage of soil salt crust; if it is determined to be an area with high coverage of soil salt crust, collecting several groups of soil salt crust samples; scanning the soil salt crust samples using a CT scanner to obtain porosity vertical distribution data, and then determining the first salt crust thickness of the soil salt crust samples; detecting the soil salt crust samples using a spectrometer to obtain spectral vertical distribution data, and then determining the second salt crust thickness of the soil salt crust samples; and determining the soil salt crust thickness in the target detection area based on the first salt crust thickness and the second salt crust thickness. By combining porosity data and spectral data, the present invention can more accurately assess the thickness of the soil salt crust, thereby improving the accuracy of detection.

Provided is a multilayer ceramic capacitor capable of improving capacitance without increasing the size of the multilayer ceramic capacitor. In a laminated ceramic capacitor (1), a first facing portion (EA) of a first internal electrode layer (31) has a first high coverage area (EA0) which is disposed further toward the outside of a laminated body (10) in a lamination direction (T) than a first lead-out portion (D1) and which has a higher coverage rate than the first lead-out portion (D1), and a second high coverage area (EA0) which is disposed further toward the outside of the laminated body (10) in a lamination direction (T) than the first lead-out portion (D1). The second opposing portion (EB) has a second high coverage area (EB0) that is disposed further toward the outside of the laminated body (10) in the lamination direction (T) than the second lead-out portion (D2) and that has a higher coverage than the coverage of the second lead-out portion (D2).

The invention relates to the technical field of intelligent visual inspection, and particularly discloses a detection device for plastic woven bag production, which comprises two groups of support plates, a pay-off roller and a wind-up roller are rotatably mounted between the two groups of support plates, and two groups of separation plates capable of alternately sliding and adjusting up and down are arranged between the pay-off roller and the wind-up roller. A wire collecting device is arranged between the separating plate and the wind-up roller, a pay-off device capable of being adjusted in a reciprocating sliding mode is installed on the wire collecting device, and the device further comprises a detection assembly. According to the invention, the multi-angle relative position of the detection assembly and the woven cloth is dynamically adjusted through the adjusting assembly, so that the problems of laser diffuse reflection interference and visual noisy points caused by grid textures and concave-convex characteristics on the surface of the woven cloth are effectively solved; by means of the multi-angle data fusion technology, the recognition sensitivity of defects such as micro broken wires, low-contrast stains and embedded hard particles is remarkably improved, high precision and high coverage rate are achieved at the same time on the premise of non-contact detection, and the misjudgment rate and the omission ratio are greatly reduced.

The present application provides a prediction method and apparatus for test space coverage. Among them, the method includes: obtaining the scene parameter mapping value of each to-be-simulated scenario in a plurality of to-be-simulated scenarios located in the test space and the preset undetected probability of the plurality of to-be-simulated scenarios; determining a preset space that is located in the corresponding mapping space of the test space and meets the preset undetected probability; determining the number of to-be-simulated scenarios belonging to the preset space according to the scene parameter mapping value of each to-be-simulated scenario; determining the coverage estimation value of the plurality of to-be-simulated scenarios for the test space according to the number of to-be-simulated scenarios belonging to the preset space. The present application solves the technical problem in the prior art that the coverage of the selected simulation scenarios for the test space cannot be known before simulating the simulation scenarios, so that more simulation scenarios are required to achieve high coverage of the test space, resulting in more simulations to be executed, and achieves the technical effect of affecting the simulation efficiency.