83results about How to "Generate accurately" patented technology

The invention discloses an autonomous evolution type 5G protocol fuzzy test system based on a large language model, and the system comprises a protocol extraction unit which employs the large language model to analyze a 5G protocol specification document, and extracts structured protocol knowledge elements containing a message format, state machine logic and parameter constraints; the vulnerability analysis unit generates a potential vulnerability description list through big language model reasoning based on the knowledge elements; the test strategy generation unit drives a large language model to generate a targeted test case based on protocol knowledge, vulnerability description and historical test knowledge in the dynamic test knowledge base; the test execution unit executes the use case and captures a result; and feeding back an analysis result of the internalization unit, extracting a causal rule, generating new test knowledge and feeding back the new test knowledge to the knowledge base. According to the system disclosed by the invention, test targets and resources can be autonomously scheduled according to continuous updating of the knowledge base, so that the test process has an iterative optimization capability, and full-process automation and intelligentization of 5G protocol fuzzy testing are realized.

This application discloses an interactive method for rapid simulation of landslide dynamics, belonging to the field of geological hazard modeling technology. The method includes the following steps: acquiring remote sensing images and topographic grids to delineate the landslide area and determine the maximum thickness of the sliding surface; calculating the distance ratio between each grid cell in the landslide area and the delineated boundary; constructing a spatial distribution model of the thickness of each grid cell based on an exponential function, maximum thickness, and distance ratio; generating a three-dimensional bed topography by combining surface topography; establishing landslide motion control equations using general control equations; and outputting simulation results by applying the landslide motion control equations through simulation tools. The spatial distribution model is based on fitting the image curve using an nth-order decay function, automatically generating the spatial distribution of image depth, improving the accuracy and convenience of the initial conditions of the landslide. The landslide motion control equations introduce an improved frictional resistance evolution model that considers the transformation from sliding to flow, effectively improving the accuracy of the landslide dynamic process simulation results.

The invention relates to the technical field of switchers, and discloses a fault analysis and information display circuit, a switcher management method and a KVM switcher, the circuit comprises a video processing module, a control module, a display module and a USB module, the USB module comprises a first processing unit, a first switching unit, a second switching unit and a second processing unit, video signal information and USB signal information can be respectively acquired through the video processing module and the USB module and transmitted to the control module, so that the control module can comprehensively integrate multi-dimensional signal data and accurately generate signal state display information or fault display information; according to the invention, signal state display information or fault display information can be displayed in real time through the display module, so that the convenience and accuracy of acquiring the state data of the switcher by a user are improved, the user can be quickly and accurately helped to position the fault of the switcher, the troubleshooting efficiency and accuracy are improved, and the use convenience and reliability of the switcher are improved.

This invention relates to the field of power system planning, and more particularly to a method and system for quantitative assessment of microgrid boundaries using multidimensional analysis and dynamic verification. The method includes: acquiring distribution network and microgrid scheme data, performing scenario identification and decoupling modeling after standardization processing; extracting end-point supply guarantee scenario data and analyzing cost elements, generating a critical cost threshold table through normalization processing and threshold approximation algorithms; constructing a multidimensional boundary index model based on this table through multidimensional parameter correlation analysis and ensemble learning training; performing benefit matching calculations and green value accounting to generate an economic benefit decomposition structure; generating an economic boundary index set by combining real-time streaming data processing and stability verification; and finally generating a standardized assessment file through matrix mapping and dynamic weight adjustment. This invention achieves dynamic quantitative assessment of the economic boundary of microgrids, effectively integrating capacity substitution benefits and green value, and providing accurate basis for planning decisions.

The application discloses a kind of wild fire smoke cluster and its boundary vector automatic identification method, system, storage medium and electronic equipment, belong to satellite remote sensing and disaster monitoring technical field.Method includes: obtaining satellite active fire point, fire event and UVAI data;Fire source area is positioned based on fire event geographic location and initial plume pixel is marked;The spatially continuous smoke cluster connected domain is identified by iterative region growing algorithm;According to the specific distribution form of connected domain pixel in satellite pixel matrix, the accurate closed boundary vector is automatically generated using matching geometric algorithm;Finally, using multiple criteria, the spatial isolated independent smoke cluster is screened out.The application avoids the defects that traditional image method is easily disturbed by environment from physical principle, realizes fully automated processing without training data, and can output vector boundary that can be directly used for diffusion and emission evaluation, significantly improves the accuracy, automation degree and application value of wild fire smoke cluster monitoring.

The application discloses a scene generation method and device based on source-load uncertainty and equipment, and relates to the technical field of energy scheduling. The method comprises the following steps: acquiring real-time source-load data of a power system; processing the real-time source-load data based on a target prediction model to obtain a multi-time-scale source-load prediction result, wherein the target prediction model is obtained by compressing the weights of a long short-term memory network prediction model; generating a collaborative scheduling strategy of source-load resources under the multi-time-scale source-load prediction result based on a multi-agent scheduling decision model; and generating a hydropower source-load scene set of the power system at different time stages under the source-load uncertainty based on the collaborative scheduling strategy. In the foregoing manner, the prediction link and the decision optimization link are closely coupled, the multi-time-scale prediction result is used to dynamically guide the reinforcement learning decision, the adaptability of the system to the source-load uncertainty is enhanced, and the organic collaboration of the multi-time-scale and the accurate generation of the uncertainty scene are realized.

The application relates to the technical field of intelligent diagnosis of vehicle-mounted operating systems, in particular to an intelligent diagnosis method and device for a vehicle-mounted operating system and a vehicle, wherein the method comprises the following steps: obtaining historical diagnosis data of the vehicle-mounted operating system, wherein the historical diagnosis data comprises at least one of historical logs, fault diagnosis results and a diagnosis rule library; performing block vectorization on the historical diagnosis data, constructing a vector database and storing the vector database in a local knowledge base, and searching current log data based on the knowledge base to obtain a search result; generating a training data set according to the fault diagnosis data and fine-tuning a large language model. The current log data and a target diagnosis task are input into the fine-tuned large language model, the fine-tuned large language model calls the local knowledge base to execute the diagnosis task, and a fault diagnosis result is generated based on the search result. Therefore, the problems that the fault diagnosis of the vehicle-mounted operating system in the related art depends on artificial experience or fixed rules, cannot dynamically fuse and intelligently infer, and is low in accuracy are solved.

The embodiment of the invention relates to the technical field of computers, and discloses a constraint perception code generation method based on multilayer verification feedback, and the method comprises the steps: obtaining a code generation request; according to the code generation request, inputting the code generation request into a code generation agent based on a constrained Markov decision process, and outputting a current code; inputting the current code into a multi-layer verification engine, and respectively performing static analysis and formalized verification to obtain a current verification result and a current feedback signal; when the current verification result is not passed, sending the current verification result and the current feedback signal to a code generation agent, iteratively executing the generation of a modified code and the static analysis and formalized verification of the multi-layer verification engine to obtain a modified verification result and a modified feedback signal, and when the verification is not passed, regenerating the code. And obtaining the target code until the verification result is that the verification is passed. According to the embodiment of the invention, the effect of accurately generating codes is realized.

Embodiments of the present disclosure disclose a resource warning method and device based on a computing node cluster and an electronic device. A specific implementation of the method comprises: determining whether to call the computing node cluster for resource processing; for each interactive object, determining the corresponding model calculation amount in the information prediction process; selecting a first computing node from the computing node cluster to support the call of each interactive object; for each interactive object, generating first historical resource overdue summary information and first future resource overdue summary information; generating second historical resource overdue summary information and second future resource overdue summary information; generating target resource quality information; and sending corresponding encrypted information to a target monitoring terminal to perform target warning under the condition that the resource quality warning condition is met. The implementation accurately and efficiently generates target resource quality information on the basis of reducing waste of computing resources through reasonable allocation of hardware resources.

The embodiment of the invention discloses an incidence relation graph adjusting method and device, equipment, a medium and a program product. A specific embodiment of the method comprises the steps of obtaining a target association relation graph; utilizing a preset object identification rule model to generate first object identification information corresponding to each piece of equipment information in the target association relation graph; according to the first object identification information, determining whether to use a pre-trained object identification information generation model to identify the same natural object; in response to determination of use, generating second object identification information corresponding to each piece of equipment information by using an object identification information generation model; and according to the second object identification information, performing graph adjustment on the target association graph to obtain an adjusted association graph. The implementation mode is related to artificial intelligence, and the same natural object identification can be accurately and effectively carried out on each piece of equipment information in the target association relation graph so as to determine each piece of natural object information corresponding to the target association relation graph.

This application discloses a video generation method, apparatus, and electronic device. Relating to the field of motion information processing, the method includes: acquiring motion video and motion data of a target user, and determining the target user's target motion; determining motion performance index values ​​for each initial video frame in the motion video based on the motion type and motion data of the target motion; performing feature recognition operations on the images of each initial video frame to obtain material feature information for each initial video frame, and determining the material performance index value for each initial video frame based on the material feature information; determining the value score for each initial video frame based on the motion performance index value and the material performance index value, and filtering the initial video frames based on the value score to obtain target video frames; and inputting the target video frames into a large language model to obtain the target video of the target motion. This application solves the problem of low efficiency in manual video processing in related technologies.

The invention relates to a qualitative and quantitative method for liensinine perchlorate. The qualitative method comprises the following steps: weighing 1mg of liensinine perchlorate and 1mg of liensinine, uniformly grinding and tabletting the liensinine perchlorate and the liensinine with 100mg of potassium bromide respectively, acquiring an infrared spectrum of 4000-400cm <-1 > by adopting an infrared spectrometer, and comparing spectrograms to find that the peak shapes of the liensinine perchlorate and the liensinine are similar, the peak shapes of the liensinine perchlorate and the liensinine perchlorate are common characteristic peaks and the peak shapes of the liensinine perchlorate are unique characteristic peaks of the liensinine perchlorate and the liensinine are common characteristic peaks and the peak shapes of the The quantitative method comprises the following steps: weighing a series of liensinine perchlorate reference substances with different masses, uniformly grinding and tabletting the liensinine perchlorate reference substances and 100mg of potassium bromide respectively, collecting an infrared spectrum, carrying out integration on a 625cm <-1 > characteristic peak to obtain a peak area, and drawing a standard curve by taking the peak area as a vertical coordinate and taking the sampling mass of the reference substances as a horizontal coordinate; the method comprises the following steps: weighing a sample to be detected, collecting an infrared spectrum, integrating a 625cm <-1 > characteristic peak to obtain a peak area, substituting the peak area into the standard curve equation, calculating the mass of the liensinine perchlorate in the sample, and substituting the mass into the content calculation formula to obtain the content of the liensinine perchlorate in the sample. The method is good in precision, repeatability and stability, wide in linear range, high in linear correlation coefficient and high in recovery rate, the problem that liensinine interference cannot be avoided in an existing content determination method is effectively solved, whether liensinine perchlorate is generated or not can be qualitatively judged, and the quantity of liensinine perchlorate generated can be quantitatively detected; and a feasible new method is provided for production process optimization and quality evaluation of liensinine perchlorate.

This application discloses a method, system, electronic device, and storage medium for processing security logs, belonging to the technical field of network security technology. The method for processing security logs includes: acquiring multiple security logs from a target device; inputting the security logs into a log bypass processing unit and a log qualitative processing unit respectively; aggregating the security logs based on the log qualitative results output by the log qualitative processing unit to obtain security alarms; qualitatively classifying the security alarms; and generating corresponding security events based on the alarm qualitative results. This application can avoid aggregating normal business behavior and malicious attack behavior in the same security alarm, accurately generating security events.

The present disclosure relates to an image processing method, a scene graph generation model training method and an electronic device, and relates to the field of image processing. The method of the present disclosure comprises: extracting one or more target pairs and information of each target pair from an image, wherein the information of each target pair comprises: feature information, position information and classification information of a first target, feature information, position information and classification information of a second target; determining a visual relationship feature of each target pair according to the information of each target pair; determining a relationship saliency of each target pair according to the visual relationship feature of each target pair; and generating a scene graph with relationship saliency corresponding to the image according to the feature information of each target, the visual relationship feature of each target pair and the relationship saliency of each target pair.

This invention discloses an automated management system and method for assembly workpiece production lines, relating to the field of cloud-edge collaborative technology. The invention integrates assembly operation observation data and cloud-edge scheduling status data, using edge compensation trigger points that have completed time-base correction as event anchor points. It constructs compensation occlusion event fragments according to assembly action affiliation and edge state version. Based on these fragments, it generates compensation occlusion results and degradation overflow fragments, and uses the degradation overflow fragments as propagation starting points to construct a compensation constraint beat propagation relationship graph, generating degradation anomaly source labels. Furthermore, it combines edge state version with cloud-edge state effective interval verification, outputting workstation scheduling restriction results, pending review scheduling instructions, scheduling cancellation results, and anomaly rollback benefit results. This system can identify hidden degradation states masked by edge compensation and reduce cloud-based scheduling control mismatch.

The invention relates to a smart home and smart property agent cooperation system and method, the system comprises a home agent, a property agent and a community agent, and the home agent is used for processing multi-modal input of a user according to a personalized decision model and generating event information according to a privacy strategy. And the property agent is used for performing task reasoning according to the event information and a preset knowledge base and generating a corresponding task instruction. And the community agent is used for executing the task instruction and feeding back an execution result to the property agent. Wherein the home agent, the property agent and the community agent perform data interaction through a preset communication architecture. The problem of how to improve the business processing efficiency while the intelligent agents of the intelligent home and the intelligent property management system cooperate in the related technology is solved.

This application belongs to the fields of artificial intelligence and fintech, and relates to an AI-based customer classification method, including: acquiring customer data and constructing a topological relationship network corresponding to the customer data; inputting the topological relationship network into a graph convolutional neural network for training to obtain a trained graph convolutional neural network; acquiring a target topological relationship network corresponding to target customer data, and processing the target topological relationship network through a customer segmentation model to generate segmentation results. This application also provides an AI-based customer classification device, computer equipment, and storage medium. Furthermore, this application relates to blockchain technology, and the customer segmentation model can be stored in the blockchain. The customer classification method of this application can be applied to user identification in the financial field, requires no labeled data for training, has low time complexity, and the use of the customer segmentation model can achieve fast and accurate generation of customer segmentation results.

The invention provides a part 3D model online generation method and system, and the method comprises the steps: obtaining the type and size parameters of a to-be-generated part inputted by a user, and generating a part 3D model through 3D design software in a resource library platform according to the type and size parameters of the to-be-generated part. Through the method, a user can select the part type and the corresponding size parameter, the accurate 3D model expected by the user can be accurately generated, searching in a library is not needed, part 3D models of various types and various specifications are rapidly generated online, and the stored most similar 3D model can be recommended.

The application provides a SMPL-X action-to-text generation method based on global and local feature fusion, and belongs to the field of artificial intelligence. The input SMPL-X action sequence is preprocessed and encoded into double-flow action features; the double-flow action features are respectively mapped to a pre-trained large language model through independent projection branches of a cross-modal mapping module to obtain global conditions and local action prefix embeddings; a text generation module takes the decoder of the pre-trained large language model as a backbone network, extracts text prompt word embeddings based on a user-given text instruction, inputs the local action prefix embeddings and the text prompt word embeddings into the decoder after splicing, and injects the global conditions into each layer of the decoder through a cross-attention mechanism to generate description text in a self-recurrent manner. The application can stably and accurately generate description text that is consistent with the semantics of the action and sufficient in details, and improves the generation stability and cross-scene applicability when the action sequence is disturbed.

The invention discloses an industrial defect image generation method and device, equipment and a medium. The method comprises the following steps: acquiring an original image of a target process; determining a target area of the original image; inputting the original image into a pre-trained target detection model, and outputting a bounding box for framing the target area by the target detection model; making a mask image corresponding to the original image, wherein the mask image comprises a mask area located in the target area; the original image, the mask image and the text prompt information are input into a pre-trained image generation model, a target defect image containing the target defect type is generated, and the image generation model is obtained through model fine tuning technology training. Therefore, the problems that defect samples in an industrial scene are scarce and various defect forms are difficult to cover are effectively solved.

This invention belongs to the technical field of 3D modeling for engineering construction. It discloses a method and system for modeling bulldozer operation maps in mining areas based on 5D Gaussian geometry. The method includes: S1 acquiring RGB images and depth data of the earthmoving operation area using an RGB-D camera; applying a contrast enhancement algorithm to the RGB data and vibration compensation to the depth data; and performing semantic recognition of the category of each pixel location; S2 back-projecting the depth data to generate a 3D point cloud; constructing 3D Gaussian units at the sampling points of the point cloud; and converting them into 5D Gaussian implicit units covering spatial, temporal, and semantic dimensions after fusing semantic category and timestamp information; generating a 3D implicit base map; S3 filtering the 5D Gaussian implicit units; and projecting to obtain a 2D rendered image. This invention provides 3D visualization support for bulldozer operation in mining areas, is applicable to scenarios such as mining, and solves modeling problems such as weak texture in earthmoving and equipment vibration interference.

This paper provides a table processing method, apparatus, electronic device, storage medium, and program product, applied in the field of human-computer interaction. The method includes: responding to receiving user input in a first table, outputting response information, whereby the user input includes table editing instructions composed of natural language, and the response information includes planning information generated based on the user input; and generating table content on a first page and / or a second page other than the first page of the first table based on the response information, whereby the table content includes at least one of the following: fields, row records, views, charts, workflows, and permission configurations. This paper solves the problems of cumbersome operation processes, low processing efficiency, and poor versatility. The corresponding beneficial effect is that it processes relevant tables based on received user input, thereby achieving intelligent table processing.

The utility model discloses a detachable long-distance adjustable cross laser positioner which comprises a front sleeve, a sliding sleeve, a rotating sleeve, a lens seat, a cylindrical lens assembly, an LD assembly and a tail fixing seat. Focal length adjustment is achieved through screw-thread fit of the rotating sleeve and the lens seat, the double-eccentric cylindrical lens group generates a cross light spot, and the long-focal-length collimating lens controls a light beam divergence angle. The LD assembly adopts a quick release structure, and supports quick replacement of a chip. The positioner has the advantages that the light beam precision is high (llt; the device has the characteristics of simple structure, convenient adjustment (+ / -5mm adjustment range), low maintenance cost (chip replacement is completed within 5 minutes) and the like, and is suitable for long-distance high-precision positioning scenes such as industrial measurement, building construction and the like.

The invention is suitable for the technical field of aluminum profile defect detection, and provides a defect identification method and system based on a new energy automobile profile, and the method comprises the steps: firstly, based on an image sensor, rapidly obtaining the internal image information and geometric dimension information of a cavity of a to-be-detected profile; then generating invisible defect detection result information according to a target detection algorithm and the internal image information of the cavity, then effectively generating size defect detection result information according to the geometric size information and preset reference size information, and finally determining the size defect of the cavity according to the invisible defect detection result information and the size defect detection result information. And defect comprehensive evaluation information is accurately generated. According to the method, efficient real-time monitoring can be carried out on the interior of the cavity of the aluminum profile, the invisible defects are accurately recognized, reliable capture of the invisible defects is achieved, continuous optimization of the aluminum profile production process and the overall quality is facilitated, and important guarantee is provided for safety and long-term reliability of key structural parts of new energy automobiles.

Embodiments of the present disclosure disclose a kind of intersection generation method, device, electronic equipment and computer readable storage medium, the method comprises: obtaining the high-precision map data in the preset road range, wherein the high-precision map data includes high-precision boundary lane line;Obtain the standard-precision map data matched with the high-precision map data, wherein the standard-precision map data includes standard-precision intersection node and standard-precision road section line;In response to the intersection of the standard-precision road section line connected with the standard-precision intersection node and the high-precision boundary lane line, then according to the standard-precision map data, generate target intersection at the intersection point of high-precision boundary lane line.This technical solution can accurately, timely and efficiently generate low-grade road intersection, so as to improve the freshness and completeness of high-precision map data, to assist the automatic driving car to accurately enter or exit corresponding intersection area, improve the user's use experience.

This invention discloses a wave generation control method and apparatus for wave generators deployed at both ends in a wave testing tank. First, the target positions and target angular frequencies of two wave trains are determined based on the target function, which can be wave attenuation, bidirectional wave generation, or focused wave generation. Then, the propagation times of the two wave trains are calculated respectively. Based on the propagation times, the target activation time of the corresponding wave generator is determined. Finally, the corresponding wave generator is activated at the target activation time, generating the corresponding waves based on the target wave height and target angular frequency. In this invention, each end of the wave generators deployed at both ends can independently control wave generation at each end. Based on the synergistic effect of the wave generators deployed at both ends, wave propagation and superposition are controlled, accurately generating focused waves and simulating the effect of concentrated waves on marine structures.

The utility model relates to the technical field of water heating equipment, and discloses an air pressure taking pipe and gas water heating equipment. The wind pressure pipeline comprises a wind pressure inner pipe and a wind pressure outer pipe, the wind pressure outer pipe is arranged outside the wind pressure inner pipe in a sleeving mode, a closed heat insulation cavity is formed between the wind pressure outer pipe and the wind pressure inner pipe, one end of the wind pressure inner pipe is communicated with the pressure tapping opening of the fan, and the other end of the wind pressure inner pipe is communicated with the wind pressure switch. By adopting the double-layer pipeline design of the wind pressure outer pipe and the wind pressure inner pipe, on one hand, external air is structurally prevented from being in direct contact with the wind pressure inner pipe, and on the other hand, heat insulation between high-temperature airflow in the wind pressure inner pipe and external low-temperature air is achieved through the heat insulation cavity in the aspect of heat transfer; the temperature difference between the inner pipe wall and the outer pipe wall of the wind pressure inner pipe is reduced, and therefore the wind pressure taking pipe can effectively restrain generation of condensate water on the inner wall of the wind pressure inner pipe, further reduces generation of the condensate water, and guarantees normal work of the wind pressure taking pipe.

This invention relates to the field of information processing, and more particularly to an earthquake event emergency response method, comprising: acquiring earthquake operational data; determining a preferred template generation method based on template correlation and report response coefficient, wherein the preferred template generation method is either reorganizing preferred templates based on regional matching averages or generating preferred templates based on information matching amplitudes; determining a report update method based on earthquake impact coefficients and public opinion information volume, wherein the report update method is either adjusting the report update frequency based on comprehensive evaluation values ​​or determining a report supplementation method based on the characteristic correlation coefficient of effective public opinion areas; the report supplementation method includes feature text supplementation and related text supplementation. This invention can improve the accuracy and timeliness of earthquake event response technical reports.

The application discloses a kind of admittance matrix generation method, device, equipment and medium, it is related to power system computing technical field, the method includes: when the operating state of first circuit is normal, obtain the first system information in first circuit, based on the self-admittance of each node in first circuit and the mutual admittance between nodes, obtain first node admittance matrix;When the operating state of first circuit is abnormal, determine the fault point of first circuit;Obtain the first fault information corresponding to the fault point;Based on first fault information and first system information, the fault equivalent impedance that negative sequence network and zero sequence network are equivalent to positive sequence network is calculated;Based on fault equivalent impedance and first fault information, the first node admittance matrix is corrected, and target node admittance matrix is obtained.The method realizes the accurate generation of admittance matrix, improves the efficiency and precision of new energy power grid short-circuit current calculation.

This invention relates to the field of computing power scheduling technology, and discloses an intelligent scheduling method and system for heterogeneous resource computing power. The method performs real-time status monitoring of heterogeneous computing resources, acquiring resource status parameters such as computing unit utilization and memory occupancy; it collects task attributes and user request parameters from the task queue, and processes historical task data based on a genetic algorithm optimization model to perform task demand prediction, generating predicted demand parameters. A dependency graph containing resource unit nodes and communication link edges is constructed using a resource topology analysis tool. The predicted demand parameters are input into a scheduling priority classifier trained by a graph neural network to identify the actual scheduling priority. Based on this priority, resource conflict prediction is performed, and the task feature vector is combined with the conflict resolution module of a fuzzy logic decision-maker to output actual conflict resolution parameters. Finally, a scheduling scheme containing resource allocation sequences and execution schedules is generated.