35results about How to "Fast iteration" patented technology

The invention relates to an engineering potential safety hazard detection method based on a multi-modal large model. The method comprises the following steps: acquiring an on-site monitoring image of a target scene; identifying a key entity in the field monitoring image, and extracting positioning information of the key entity; generating a depth map based on the on-site monitoring image; based on the positioning information of the key entity, combining with the depth map, associating the positioning information and the depth information for the key entity, and generating a scene description text; based on the on-site monitoring image, the depth map corresponding to the on-site monitoring image and the scene description text, constructing a multi-modal input packet; inputting the multi-modal input packet into a learned engineering safety domain knowledge base and a visual language large model subjected to instruction fine tuning, and outputting a hidden danger judgment result; the instruction fine tuning of the visual language large model is based on a hidden danger inference chain data set, the data set has hidden danger images corresponding to hidden danger items in an engineering safety field knowledge base and annotation data of each hidden danger image, and the annotation data comprises step result data corresponding to each hidden danger detection step.

This invention provides a method, apparatus, intelligent agent, electronic device, and storage medium for equipment performance testing, belonging to the field of intelligent manufacturing technology. The method includes: obtaining the maximum cycle time of the production line where the target equipment is located; obtaining a candidate detection instruction set, which contains multiple independent atomic detection instructions, each instruction configured with a risk weight value, execution time, and execution correlation; selecting target atomic detection instructions from the candidate detection instruction set and arranging them to generate a target detection instruction sequence, with the optimization objective being to maximize the total risk weight value and the constraints being that the total execution time does not exceed the maximum cycle time and the execution correlation is satisfied; and sending the sequence to the target equipment. This invention achieves decoupling of the detection logic and the electronic control firmware by atomically decoupling the detection instructions and generating the detection sequence based on multi-constraint dynamic programming, supporting rapid iteration of the detection strategy, and maximizing quality risk coverage within a limited cycle time.

The application discloses a method and device for constructing hydraulic simulation data. The method comprises: determining a hydraulic role corresponding to each visible component in a BIM model; determining a first face dictionary, a connection element dictionary and a connection face list based on the determination result of the hydraulic role; processing bottom surface data and top surface data of the visible component whose corresponding hydraulic role is a connection element based on the connection element dictionary to determine a receiving area set and a centroid point set; determining a support DEM dictionary and a blocking DEM dictionary based on the first face dictionary, and determining a final support DEM dictionary based on the determined support DEM dictionary and the determined blocking DEM dictionary; and determining a connection DEM dictionary based on the first face dictionary and the connection face list. Thus, the conversion efficiency from the BIM model to the hydraulic simulation is improved.

This invention relates to a method and system for automated generation of TSN network configurations based on a reflective agent. The system comprises a network state perception and intent reflection module, a YANG model configuration parameter and structure decision module, and a YANG model intelligent generation module. The network state perception and intent reflection module is responsible for structurally perceiving network state and resource information. The YANG model configuration parameter and structure decision module integrates multi-source knowledge and contextual information, intelligently generating deployable TSN scheduling parameters and YANG configuration structures based on business needs. The YANG model intelligent generation module automatically generates the corresponding YANG configuration model based on the optimized results, performs syntax and semantic verification, and then distributes it to the target device, achieving automated deployment of network configurations. This invention significantly improves the intelligence level and deployment automation capability of TSN network configuration by introducing reflective reasoning and feedback optimization techniques.

The application provides a six-dimensional force sensor optimization method based on CM-PINN, which depends on a six-dimensional force sensor optimization model based on CM-PINN. The application realizes the structured hard constraint of the flexibility matrix by embedding the B matrix projection into the CM-PINN network, replaces the traditional loss function soft constraint, ensures that the mechanical properties relied on in the optimization process always strictly meet the geometric symmetry and the inherent physical law of the flexibility matrix, fundamentally eliminates the physical violation phenomenon from the architecture level, makes the optimization result more consistent with the engineering actual mechanical properties, and improves the optimization reliability; through the design of the load special branch and the symmetric joint training mechanism, the strong high-dimensional nonlinear coupling problem between the elastomer mechanical properties and the external load, the geometric structure parameters is effectively solved. The method can greatly reduce the calculation cost, shorten the design cycle, realize the efficient global optimization of the sensor geometric parameters and the load range, and adapt to the design requirements of the engineering end rapid iteration and rapid verification.

The application discloses a style legal consultation question and answer method and system, a storage medium and equipment, relates to the technical field of natural language processing, and the method comprises the following steps: collecting text data and audio and video data in the legal consultation field and converting the text data and audio and video data into texts; generating structured text data sets from the texts by using a base model; dividing the structured text data sets into a basic legal knowledge base and a stylized knowledge base according to the style categories of seed instructions; adopting different styles of vertical field labeled training sets, and obtaining a pre-training fine-tuning model by fine-tuning the base model based on a low-rank approximation fine-tuning method; and generating a corresponding style answer from the pre-training fine-tuning model according to a received user legal consultation question. Through the technical scheme of the application, the stylized model can be iterated more quickly, the low-delay question and answer demand is realized, the legal consultation reply can be provided according to the style preferred by the user, and the work efficiency of legal consultation is improved.

This application discloses a method, system, device, and medium for improving the activation rate of intelligent driving functions. The method includes: receiving user behavior data and vehicle status data sent by the vehicle; constructing a user profile based on the user behavior data and vehicle status data, and identifying key negative scenarios affecting the activation rate; generating an intelligent driving function activation guidance strategy based on the user profile and the key negative scenarios; and pushing the intelligent driving function activation guidance strategy to the vehicle, so that the vehicle activates the intelligent driving function according to the strategy. This application achieves precise personalization and rapid iteration of the guidance strategy, thereby systematically and efficiently improving the user activation rate of intelligent driving functions.

The application discloses a low-redundancy minimal data table design method and system for industrial ERP / MES, and belongs to the technical field of industrial digitization and database architecture. The application realizes low redundancy, low association, high performance and easy maintenance of the data table through full-service field collection, default single-table aggregation, controllable split constraint, weak association mapping, unified data entry and minimal query control. The application forces single-table priority, splits at most into two tables, and performs at most one association in regular query, thereby solving the problems of excessive split, complex association, poor performance and difficult maintenance in traditional design from the root, and has the advantages of minimalism, high efficiency, stability and easy expansion, and is suitable for various ERP / MES / WMS industrial management systems and has been applied in actual production environment.

The application discloses an education facility site selection and configuration optimization method and system, computer equipment and a medium. The method comprises the following steps: acquiring data of a target area and preprocessing; performing primary school education facility supply analysis and resident demand analysis based on township primary school education facility supply data and rural community life power supply data, and measuring the supply and demand accessibility of primary school education facilities; performing population flow measurement of different time scales based on the rural community life power supply data; performing K-means clustering analysis according to the supply and demand accessibility, the population monthly flow level and the population annual flow level, and obtaining clustering results; matching the clustering results with rural community units, identifying the layout characteristics and types of rural community primary school education facilities, and realizing targeted township primary school education facility site selection and configuration optimization in units of rural communities. The application can provide primary school education facility site selection and configuration optimization by replacing the previous population census data.

This utility model relates to the field of infrared detection technology, specifically to a portable intelligent infrared diagnostic instrument. It includes a housing and an infrared lens mounted on the upper part of the housing, as well as a clamp mounted on the lower part of the housing and a downward-protruding platform on the lower left or right side of the housing. The clamp includes a fixed base plate on the lower part of the housing, a rear baffle fixed to the rear end of the fixed base plate, a front baffle spaced at the front end of the fixed base plate, a mounting hole and an adjusting screw hole on the front end of the fixed base plate, a clamping spring and a guide rod in the mounting hole, an adjusting through hole on the front baffle, an adjusting screw in the adjusting through hole, and a knob on the outer end of the adjusting screw. This design achieves stable clamping of the infrared diagnostic instrument to a smartphone through the clamp, and enables data communication with the phone via a Type-C connector. It fully utilizes the powerful computing capabilities and rich interface resources of the smartphone, achieving a miniaturized, lightweight, and high-performance infrared diagnostic instrument.

The invention discloses a Jenkins-Kubernetes interactive encryption method, a storage medium, an integrated architecture system and a vehicle, and the Jenkins-Kubernetes interactive encryption method comprises the following steps: when Jenkins executes a deployment task, calling and executing a predefined shell script; the method comprises the following steps: generating a temporary Docker honeypot on the basis of a predefined shell script, the temporary Docker honeypot comprising a Kubectl and a Kubecfig certificate, so that the Kubectl calls a Kubecnetes API (Application Program Interface) through the Kubecfig certificate to interact with Kubecnetes, and then deleting the Kubecfig certificate on the basis of the predefined shell script and releasing the Docker honeypot. Therefore, the communication security of integration of Jenkins and Kubernetes is remarkably enhanced, the high risk of local storage of a Kubsecfig certificate is avoided, external attacks and internal leakage risks are effectively resisted, meanwhile, the high efficiency and flexibility of a CI / CD process are kept, and a solid foundation is provided for rapid iteration and secure delivery of cloud native applications.

This invention relates to the field of computational electromagnetics, specifically to an antenna layout modeling and analysis method based on coupled rays and current basis. The method includes: defining electrically small and electrically large regions of the electrically large carrier antenna layout target and generating mesh data; assembling the system matrix within the electrically small regions; accurately aggregating all illuminated areas within the electrically large regions using backward ray tracing technology; establishing a cyclic iterative mode for the electrically small and electrically large outer surface currents; obtaining the overall stable current distribution on the outer surface based on the residual convergence results of the currents in the electrically small regions; and finally solving for the antenna layout performance characteristics affected by the coupled electrically large carrier currents. This invention effectively improves the accuracy and efficiency problems of the traditional integral-ray hybrid method, and enhances the design efficiency of electrically large carrier antenna layouts.

The invention discloses a verification system, method and device for hybrid power control software and a medium, and the system comprises a virtual vehicle model which is used for simulating the operation state of a target vehicle on a road, and outputting an analog signal; the signal transceiving processing module is used for converting the analog signal into an input signal which can be identified by a control software module and converting an output signal of the control software module into a driving signal which can be identified by the virtual vehicle model; the control software module is used for receiving the input signal and generating the output signal after enabling through a preset control strategy so as to control a power element in the virtual vehicle model; wherein the virtual vehicle model and the signal transceiving processing module are used for verifying the control software module on the basis of the analog signal and the driving signal.

The invention relates to an ultrasonic spraying process parameter rapid calibration method and system based on dye tracing and image analysis. The method comprises the following steps that selected dye is added into a spraying solution to serve as a tracer agent; ultrasonic spraying equipment is used for spraying on the base material according to preset parameters to form a colored coating; sampling in an effective film forming area of the coating by adopting a standard nine-point method; collecting a color image of each sampling point, and extracting and calculating a color characteristic value corresponding to the color of the tracer agent; based on the average value and the standard deviation of the characteristic values of all the sampling points, the relative thickness and the uniformity of the coating are quantitatively evaluated respectively; and through multiple groups of parameter experiments, a quantitative relation model of the process parameters, the average value and the standard deviation is established, so that an optimal process parameter window is determined. According to the method, dye tracing is adopted, and a low-cost image acquisition and processing means is combined, so that rapid, visual and quantitative calibration of ultrasonic spraying process parameters is realized, and the method is particularly suitable for rapid iterative optimization in process research, development and debugging stages.

This application discloses a collaborative planning method for UAV swarm ground attack missions, comprising: S1 randomly distributing the UAV swarm over a designated area and assessing the relative states of the UAVs and ground targets; S2 assigning targets to the swarm of m UAVs and n ground targets based on a mission benefit calculation method; S3 planning the flight path of each UAV to the target using the Dubins path planning method based on the situation assessment results and the target assignment scheme; and S4 replanning threatened paths, considering obstacle threats. This invention addresses the problems of assessing the situation, assigning corresponding tasks, and planning the shortest path when multiple UAVs are performing ground attack missions.

The application discloses a query process configuration method and device, equipment, medium and product, and the method comprises the following steps: acquiring query configuration information pushed by a query end; calling a business verification module to verify business characteristic information; when the business characteristic information meets the business verification rule, acquiring a multiplexing plug-in identifier or a newly configured plug-in in plug-in configuration information; based on context information contained in the plug-in configuration information, concatenating a multiplexing plug-in corresponding to the multiplexing plug-in identifier or a newly configured plug-in to generate a corresponding plug-in execution process chain; executing the plug-in execution process chain based on self-defined function information, calling a search engine to query target business data stored in a corresponding database, generating query result information containing the target business data, and configuring one or more alarm modules to monitor the execution process of the plug-in execution process chain according to alarm configuration information. The application provides a simple query process configuration service for a platform, and combines a framework to quickly deploy a business data query process scene.

The invention provides an electronic signal reconnaissance equipment construction method and device and a storage medium, and belongs to the technical field of equipment construction, and the method comprises the steps: importing electronic signal reconnaissance equipment construction demand data, and obtaining a radio frequency link parameter set from a pre-constructed radio frequency link database according to the electronic signal reconnaissance equipment construction demand data; obtaining a multi-channel signal processing parameter set from a pre-constructed multi-channel signal processing database according to the construction demand data of the electronic signal reconnaissance equipment; and gathering the radio frequency link parameter set and the multichannel signal processing parameter set to obtain a to-be-processed reconnaissance equipment construction data set. According to the invention, the problems of large size, high weight and large signal transmission loss under the traditional discrete board-level integrated architecture are solved, and the PCB design cycle is shortened, the cost is reduced, and the function upgrading process is simplified; the problems of long development period, poor compatibility and adaptability and low anti-electromagnetic interference capability of multi-channel signal sampling and signal processing functions are solved.

The application discloses a 'rolling-grinding-honing' multi-process parameter collaborative optimization and decision method, which comprises the following steps: 1) according to the characteristics of gear machining process in the automobile high-speed gear machining process, selecting process parameter variables to be optimized, and constructing a 'rolling-grinding-honing' process optimization model; 2) using a multi-objective snake optimization algorithm to iteratively solve the 'rolling-grinding-honing' process optimization model, and obtaining a Pareto collaborative process parameter solution set; 3) based on an entropy weight-TOPSIS decision method, evaluating and sorting the Pareto collaborative process parameter solution set, and obtaining optimal process parameters. The application solves the problem of how to obtain the overall optimal solution in the machining process rather than a single process optimal solution in the new energy automobile high-speed gear machining process.

The invention provides an exhaust system of an injection mold, and relates to the technical field of exhaust of injection molds. The multi-mode gas detection module is adopted, multiple sets of composite sensors are arranged in a key area of a cavity through a distributed sensing network, and real-time and accurate collection of gas state parameters such as pressure, temperature and flow velocity in the cavity is achieved; the exhaust control module constructs a dynamic model based on collected data, noise reduction processing is carried out through a Kalman filtering algorithm to guarantee data reliability, a self-adaptive exhaust strategy is generated in combination with a reinforcement learning algorithm and a process knowledge base, and a multi-stage exhaust valve of the grading execution module can adjust the opening degree in a stepless mode according to the gas pressure gradient. The negative pressure auxiliary unit can provide precise negative pressure in the high-speed injection stage, efficient exhaust of gas of different materials under different working conditions is achieved, and the defect rate of gas marks, shrinkage cavities, scorching and the like of products is reduced.

The application belongs to the field of control panel design, and particularly relates to a reconfigurable switch control panel for ergonomics evaluation. Two opposite side walls in the box body are respectively provided with L-shaped mounting parts; two guide columns are respectively mounted on the corresponding L-shaped mounting parts; two springs are respectively mounted on the corresponding guide columns; the two ends of an iron base are respectively provided with lugs which are mounted on the guide columns, and the bottom of the iron base is provided with a rotatable fixed handle; after the iron base and the springs are compressed from the upper limit position to the lower limit position, the iron base is positioned at the lower limit position by rotating the rotatable fixed handle and limiting with the L-shaped mounting part, and a magnet is mounted on the iron base; an aluminum panel is mounted on the outer surface of the box body; a hardware control switch is located on the aluminum panel, and the hardware control switch is positioned by the magnetic attraction between an iron mounting seat on the hardware control switch and the magnet.

The invention provides a helicopter main reducer rigidity collaborative optimization method based on an orthogonal test, and belongs to the technical field of gear transmission. The method comprises the following steps: determining key parameters of the helicopter main reducer transmission system; respectively calculating the torsional rigidity, the supporting rigidity and the meshing rigidity of the transmission system; constructing a helicopter main reducer transmission system quasi-statics model based on the deformation coordination condition; in combination with orthogonal experimental design, multi-level experimental design is carried out on stiffness parameters of each level, a system uniform load coefficient is solved through a quasi-statics program, key influence factors and optimization level are determined by utilizing range analysis, and finally collaborative optimization of the system stiffness is realized. By systematically analyzing the influence of each rigidity on the uniform load coefficient of the system, collaborative optimization of the rigidity of the helicopter main speed reducer transmission system is realized, and the uniform load characteristic of the helicopter main speed reducer transmission system is improved.

The invention discloses a wheat breeding method, and relates to the technical field of crop intelligent breeding, and the method comprises the following steps: S1, obtaining a whole genome DNA sample of a wheat germplasm to be bred and plant tissues in different growth periods, detecting genome variation sites through a liquid phase breeding chip, and analyzing a gene space expression mode by combining a space-time transcriptome technology, a multispectral unmanned aerial vehicle and a root system in-situ sensor are used for collecting phenotype data, and a genotype and phenotype association database is established. According to the wheat breeding method provided by the invention, by integrating genomics, phenotypic omics and artificial intelligence technologies, the precision and intelligence of the breeding process are realized, the breeding efficiency and the achievement quality are remarkably improved, the dependence of traditional breeding on phenotypic selection is broken through, a genetic mechanism formed by crop traits can be comprehensively analyzed, and the method is suitable for popularization and application. And the matching relationship between the genetic loci and the environmental factors is accurately evaluated, so that a more scientific and reasonable breeding scheme is designed.

The invention discloses a digital mission engineering development method based on a meta-model library. The digital mission engineering development method is used for modeling of a maritime search and rescue task complex system. The method comprises the following steps: constructing a system model for currently input maritime search and rescue task data and modeling problems based on a pre-constructed meta-model library of a maritime search and rescue task system; according to the method, standardized processes of digital mission engineering are set, including activities including scene conception, mission definition, process analysis, resource generation, experimental design, simulation deduction and evaluation optimization, the activities are refined into action sequences, each action is clearly defined, and a standard method and a working template are provided for the digital mission engineering. According to the method, the problems of incomplete scene description, unclear mission definition, nonstandard architecture design, insufficient verification and evaluation and the like during modeling of the maritime search and rescue system are solved, the standardized process of modeling of the maritime search and rescue task system is realized, the modeling speed and precision are improved, and rapid generation and iteration of system modeling in different scenes are supported.

This utility model relates to an electrolyzer device and hydrogen production equipment, which includes a support assembly, an electrolyzer assembly, and a hydraulic assembly. The electrolyzer assembly includes multiple electrolysis chambers arranged sequentially along a first direction, and each electrolysis chamber is slidably connected to the support assembly; the power output end of the hydraulic assembly is fixedly connected to one end of the electrolyzer assembly; and the hydraulic assembly can drive the electrolysis chambers to move along the first direction. In the above-mentioned electrolyzer device and hydrogen production equipment, since the power output end of the hydraulic assembly is fixedly connected to one end of the electrolyzer assembly, the movement of the electrolysis chambers along the first direction can be achieved by driving the hydraulic assembly, thereby changing the distance between the multiple electrolysis chambers, thus realizing the rapid sealing or disassembly of the electrolyzers, making the disassembly and assembly efficiency of the entire electrolyzer high, thereby improving the development progress of the electrolyzer and meeting the needs for rapid testing, rapid iteration, rapid development and market launch of new materials and new products.

This invention relates to a two-stage federated distillation and large model fine-tuning method based on differential privacy, belonging to the fields of artificial intelligence security, federated learning, and differential privacy technology. The method includes: Step 1, federated pre-training based on complexity adaptive budget management and momentum orthogonal subspace directional noise addition; Step 2, local dataset distillation based on frequency domain-aware complex plane anisotropy noise addition; and Step 3, cloud-based large model fine-tuning and end-to-end privacy compliance assessment based on noise prior-driven adaptive rank. This invention achieves precise allocation and tracking of the privacy budget in both the federated pre-training and data distillation stages by introducing mathematically provable RDP differential privacy protection. It completes high-fidelity generation of the distilled dataset and secure large model fine-tuning while strictly protecting the privacy of the client's original data, which is of great significance for promoting the secure and efficient deployment of large models in distributed privacy-sensitive environments.

The present application relates to a kind of physical reinforcement neural network-based fabric constitutive parameter fast identification method, comprising the following steps: 1), the macroscopic tensile, shear and bending test are carried out to the fabric sample to be identified, while collecting microstructure image, obtain multiscale feature dataset;2), physical reinforcement neural network model forward inference: the multiscale feature dataset is input into pre-trained physical reinforcement neural network;3), the complete constitutive parameter vector of target fabric is inferred and output by physical reinforcement neural network model;4), physical consistency verification: with constitutive parameter vector as input, drive finite element simulation, compare quantitatively the mechanical response curve of simulation output and measured curve, if error exceeds threshold value, then trigger adaptive fine-tuning process;5), physical reinforcement neural network model is continuously trained and updated.The present application can realize the constitutive parameter identification of fast, small sample, high precision for new variety fabric.

This invention proposes an integrated touch display testing device and system, belonging to the field of automated testing technology for flat panel displays and touch modules. The system includes: a network construction module: identifying multiple interface protocols of the touch display module and generating interface compatibility data; dynamically configuring LVDS, MIPI, and EDP multi-channel transmission links based on the interface compatibility data to construct an adaptive interface communication network; this integrated touch display testing method significantly improves the compatibility of the testing equipment with multi-protocol modules such as LVDS, MIPI, and EDP through multi-interface adaptive transmission technology, eliminating test interruption problems caused by interface incompatibility.

The application relates to a music recommendation method and system fusing deep audio semantics and collaborative filtering, which comprises the following steps: receiving an original audio signal for pretreatment; inputting a preset deep neural network model to obtain a deep audio semantic feature vector; collecting music interaction behavior data of all users and constructing a user-song interaction matrix; adopting a preset matrix decomposition technology to decompose the user-song interaction matrix into a user latent factor matrix and a song latent factor matrix; when in a music recommendation scene, calculating a content-based music recommendation score according to the deep audio semantic feature vector, and calculating a collaborative filtering prediction score according to the user latent factor matrix and the song latent factor matrix; fusing the music recommendation score and the collaborative filtering prediction score to obtain a fusion recommendation score, and performing music recommendation according to the fusion recommendation score. Through the fusion of deep audio semantic analysis and collaborative filtering, the accuracy and novelty of music recommendation are improved.

The invention belongs to the field of automatic control technology and multi-agent system cooperative control, and particularly relates to a multi-agent system fault-tolerant inclusion control method and system based on a neural network, and the control method comprises the following steps: S1, constructing a second-order multi-agent system; s2, constructing a full connection-fuzzy neural network; performing high-precision online fitting and approximation on non-ideal factors in the second-order multi-agent system to generate corresponding compensation items; s3, constructing a fixed time state observer, and estimating unknown position states and speed states of all the following intelligent agents within a preset time upper limit irrelevant to the initial state of the system; s4, constructing a fixed time sliding mode control law based on the estimation state and the compensation item; and S5, applying a fixed time sliding mode control law to the following agents, so that all the following agents converge and are stabilized in a dynamic convex hull formed by a plurality of leader states within a fixed time, and realizing inclusion control. According to the invention, the risk in practical application can be effectively reduced.

The present disclosure relates to the technical field of computer, and particularly relates to a query request response method and device, equipment and storage medium, which are applied to query response of enterprise internal data resources, comprising: obtaining a query request input by a user, performing intent understanding and context analysis on the query request, and generating an intent analysis result containing query semantics, task type and preliminary sub-task disassembly result; generating an agent scheduling instruction based on the intent analysis result; the agent scheduling instruction is used to call at least one sub-agent in a data query agent, a root cause analysis agent or an intelligent decision agent; according to the agent scheduling instruction, a corresponding data query, root cause analysis or decision suggestion generation operation is performed by the scheduled sub-agent to obtain a sub-agent execution result; whether the sub-agent needs to be continuously scheduled is evaluated according to the sub-agent execution result, at least one agent in the data query agent, the root cause analysis agent or the intelligent decision agent is called in a loop when the sub-agent needs to be continuously scheduled, until a task termination condition is met, and an intelligent analysis report is obtained; and the intelligent analysis report is displayed.